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

NASA Astrophysics Data System (ADS)

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.

Improving target coverage and organ-at-risk sparing in intensity-modulated radiotherapy for cervical oesophageal cancer using a simple optimisation method.

PubMed

Lu, Jia-Yang; Cheung, Michael Lok-Man; Huang, Bao-Tian; Wu, Li-Li; Xie, Wen-Jia; Chen, Zhi-Jian; Li, De-Rui; Xie, Liang-Xi

2015-01-01

To assess the performance of a simple optimisation method for improving target coverage and organ-at-risk (OAR) sparing in intensity-modulated radiotherapy (IMRT) for cervical oesophageal cancer. For 20 selected patients, clinically acceptable original IMRT plans (Original plans) were created, and two optimisation methods were adopted to improve the plans: 1) a base dose function (BDF)-based method, in which the treatment plans were re-optimised based on the original plans, and 2) a dose-controlling structure (DCS)-based method, in which the original plans were re-optimised by assigning additional constraints for hot and cold spots. The Original, BDF-based and DCS-based plans were compared with regard to target dose homogeneity, conformity, OAR sparing, planning time and monitor units (MUs). Dosimetric verifications were performed and delivery times were recorded for the BDF-based and DCS-based plans. The BDF-based plans provided significantly superior dose homogeneity and conformity compared with both the DCS-based and Original plans. The BDF-based method further reduced the doses delivered to the OARs by approximately 1-3%. The re-optimisation time was reduced by approximately 28%, but the MUs and delivery time were slightly increased. All verification tests were passed and no significant differences were found. The BDF-based method for the optimisation of IMRT for cervical oesophageal cancer can achieve significantly better dose distributions with better planning efficiency at the expense of slightly more MUs.

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

NASA Astrophysics Data System (ADS)

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.

Fault-tolerant optimised tracking control for unknown discrete-time linear systems using a combined reinforcement learning and residual compensation methodology

NASA Astrophysics Data System (ADS)

Han, Ke-Zhen; Feng, Jian; Cui, Xiaohong

2017-10-01

This paper considers the fault-tolerant optimised tracking control (FTOTC) problem for unknown discrete-time linear system. A research scheme is proposed on the basis of data-based parity space identification, reinforcement learning and residual compensation techniques. The main characteristic of this research scheme lies in the parity-space-identification-based simultaneous tracking control and residual compensation. The specific technical line consists of four main contents: apply subspace aided method to design observer-based residual generator; use reinforcement Q-learning approach to solve optimised tracking control policy; rely on robust H∞ theory to achieve noise attenuation; adopt fault estimation triggered by residual generator to perform fault compensation. To clarify the design and implementation procedures, an integrated algorithm is further constructed to link up these four functional units. The detailed analysis and proof are subsequently given to explain the guaranteed FTOTC performance of the proposed conclusions. Finally, a case simulation is provided to verify its effectiveness.

Close packing in curved space by simulated annealing

NASA Astrophysics Data System (ADS)

Wille, L. T.

1987-12-01

The problem of packing spheres of a maximum radius on the surface of a four-dimensional hypersphere is considered. It is shown how near-optimal solutions can be obtained by packing soft spheres, modelled as classical particles interacting under an inverse power potential, followed by a subsequent hardening of the interaction. In order to avoid trapping in high-lying local minima, the simulated annealing method is used to optimise the soft-sphere packing. Several improvements over other work (based on local optimisation of random initial configurations of hard spheres) have been found. The freezing behaviour of this system is discussed as a function of particle number, softness of the potential and cooling rate. Apart from their geometric interest, these results are useful in the study of topological frustration, metallic glasses and quasicrystals.

Multiobjective optimisation of bogie suspension to boost speed on curves

NASA Astrophysics Data System (ADS)

Milad Mousavi-Bideleh, Seyed; Berbyuk, Viktor

2016-01-01

To improve safety and maximum admissible speed on different operational scenarios, multiobjective optimisation of bogie suspension components of a one-car railway vehicle model is considered. The vehicle model has 50 degrees of freedom and is developed in multibody dynamics software SIMPACK. Track shift force, running stability, and risk of derailment are selected as safety objective functions. The improved maximum admissible speeds of the vehicle on curves are determined based on the track plane accelerations up to 1.5 m/s2. To attenuate the number of design parameters for optimisation and improve the computational efficiency, a global sensitivity analysis is accomplished using the multiplicative dimensional reduction method (M-DRM). A multistep optimisation routine based on genetic algorithm (GA) and MATLAB/SIMPACK co-simulation is executed at three levels. The bogie conventional secondary and primary suspension components are chosen as the design parameters in the first two steps, respectively. In the last step semi-active suspension is in focus. The input electrical current to magnetorheological yaw dampers is optimised to guarantee an appropriate safety level. Semi-active controllers are also applied and the respective effects on bogie dynamics are explored. The safety Pareto optimised results are compared with those associated with in-service values. The global sensitivity analysis and multistep approach significantly reduced the number of design parameters and improved the computational efficiency of the optimisation. Furthermore, using the optimised values of design parameters give the possibility to run the vehicle up to 13% faster on curves while a satisfactory safety level is guaranteed. The results obtained can be used in Pareto optimisation and active bogie suspension design problems.

H2/H∞ control for grid-feeding converter considering system uncertainty

NASA Astrophysics Data System (ADS)

Li, Zhongwen; Zang, Chuanzhi; Zeng, Peng; Yu, Haibin; Li, Shuhui; Fu, Xingang

2017-05-01

Three-phase grid-feeding converters are key components to integrate distributed generation and renewable power sources to the power utility. Conventionally, proportional integral and proportional resonant-based control strategies are applied to control the output power or current of a GFC. But, those control strategies have poor transient performance and are not robust against uncertainties and volatilities in the system. This paper proposes a H2/H∞-based control strategy, which can mitigate the above restrictions. The uncertainty and disturbance are included to formulate the GFC system state-space model, making it more accurate to reflect the practical system conditions. The paper uses a convex optimisation method to design the H2/H∞-based optimal controller. Instead of using a guess-and-check method, the paper uses particle swarm optimisation to search a H2/H∞ optimal controller. Several case studies implemented by both simulation and experiment can verify the superiority of the proposed control strategy than the traditional PI control methods especially under dynamic and variable system conditions.

On the analysis of using 3-coil wireless power transfer system in retinal prosthesis.

PubMed

Bai, Shun; Skafidas, Stan

2014-01-01

Designing a wireless power transmission system(WPTS) using inductive coupling has been investigated extensively in the last decade. Depending on the different configurations of the coupling system, there have been various designing methods to optimise the power transmission efficiency based on the tuning circuitry, quality factor optimisation and geometrical configuration. Recently, a 3-coil WPTS was introduced in retinal prosthesis to overcome the low power transferring efficiency due to low coupling coefficient. Here we present a method to analyse this 3-coil WPTS using the S-parameters to directly obtain maximum achievable power transferring efficiency. Through electromagnetic simulation, we brought a question on the condition of improvement using 3-coil WPTS in powering retinal prosthesis.

A New Multiconstraint Method for Determining the Optimal Cable Stresses in Cable-Stayed Bridges

PubMed Central

Asgari, B.; Osman, S. A.; Adnan, A.

2014-01-01

Cable-stayed bridges are one of the most popular types of long-span bridges. The structural behaviour of cable-stayed bridges is sensitive to the load distribution between the girder, pylons, and cables. The determination of pretensioning cable stresses is critical in the cable-stayed bridge design procedure. By finding the optimum stresses in cables, the load and moment distribution of the bridge can be improved. In recent years, different research works have studied iterative and modern methods to find optimum stresses of cables. However, most of the proposed methods have limitations in optimising the structural performance of cable-stayed bridges. This paper presents a multiconstraint optimisation method to specify the optimum cable forces in cable-stayed bridges. The proposed optimisation method produces less bending moments and stresses in the bridge members and requires shorter simulation time than other proposed methods. The results of comparative study show that the proposed method is more successful in restricting the deck and pylon displacements and providing uniform deck moment distribution than unit load method (ULM). The final design of cable-stayed bridges can be optimised considerably through proposed multiconstraint optimisation method. PMID:25050400

A new multiconstraint method for determining the optimal cable stresses in cable-stayed bridges.

PubMed

Asgari, B; Osman, S A; Adnan, A

2014-01-01

Cable-stayed bridges are one of the most popular types of long-span bridges. The structural behaviour of cable-stayed bridges is sensitive to the load distribution between the girder, pylons, and cables. The determination of pretensioning cable stresses is critical in the cable-stayed bridge design procedure. By finding the optimum stresses in cables, the load and moment distribution of the bridge can be improved. In recent years, different research works have studied iterative and modern methods to find optimum stresses of cables. However, most of the proposed methods have limitations in optimising the structural performance of cable-stayed bridges. This paper presents a multiconstraint optimisation method to specify the optimum cable forces in cable-stayed bridges. The proposed optimisation method produces less bending moments and stresses in the bridge members and requires shorter simulation time than other proposed methods. The results of comparative study show that the proposed method is more successful in restricting the deck and pylon displacements and providing uniform deck moment distribution than unit load method (ULM). The final design of cable-stayed bridges can be optimised considerably through proposed multiconstraint optimisation method.

Techniques d'inspection par ondes guidees ultrasonores d'assemblages brases dans des reacteurs aeronautiques =

NASA Astrophysics Data System (ADS)

Comot, Pierre

L'industrie aeronautique, cherche a etudier la possibilite d'utiliser de maniere structurelle des joints brases, dans une optique de reduction de poids et de cout. Le developpement d'une methode d'evaluation rapide, fiable et peu couteuse pour evaluer l'integrite structurelle des joints apparait donc indispensable. La resistance mecanique d'un joint brase dependant principalement de la quantite de phase fragile dans sa microstructure. Les ondes guidees ultrasonores permettent de detecter ce type de phase lorsqu'elles sont couplees a une mesure spatio-temporelle. De plus la nature de ce type d'ondes permet l'inspection de joints ayant des formes complexes. Ce memoire se concentre donc sur le developpement d'une technique basee sur l'utilisation d'ondes guidees ultrasonores pour l'inspection de joints brases a recouvrement d'Inconel 625 avec comme metal d'apport du BNi-2. Dans un premiers temps un modele elements finis du joint a ete utilise pour simuler la propagation des ultrasons et optimiser les parametres d'inspection, la simulation a permis egalement de demontrer la faisabilite de la technique pour la detection de la quantite de phase fragile dans ce type de joints. Les parametres optimises sont la forme de signal d'excitation, sa frequence centrale et la direction d'excitation. Les simulations ont montre que l'energie de l'onde ultrasonore transmise a travers le joint aussi bien que celle reflechie, toutes deux extraites des courbes de dispersion, etaient proportionnelles a la quantite de phase fragile presente dans le joint et donc cette methode permet d'identifier la presence ou non d'une phase fragile dans ce type de joint. Ensuite des experimentations ont ete menees sur trois echantillons typiques presentant differentes quantites de phase fragile dans le joint, pour obtenir ce type d'echantillons differents temps de brasage ont ete utilises (1, 60 et 180 min). Pour cela un banc d'essai automatise a ete developpe permettant d'effectuer une analyse similaire a celle utilisee en simulation. Les parametres experimentaux ayant ete choisis en accord avec l'optimisation effectuee lors des simulations et apres une premiere optimisation du procede experimental. Finalement les resultats experimentaux confirment les resultats obtenus en simulation, et demontrent le potentiel de la methode developpee.

Optimal integrated management of groundwater resources and irrigated agriculture in arid coastal regions

NASA Astrophysics Data System (ADS)

Grundmann, J.; Schütze, N.; Heck, V.

2014-09-01

Groundwater systems in arid coastal regions are particularly at risk due to limited potential for groundwater replenishment and increasing water demand, caused by a continuously growing population. For ensuring a sustainable management of those regions, we developed a new simulation-based integrated water management system. The management system unites process modelling with artificial intelligence tools and evolutionary optimisation techniques for managing both water quality and water quantity of a strongly coupled groundwater-agriculture system. Due to the large number of decision variables, a decomposition approach is applied to separate the original large optimisation problem into smaller, independent optimisation problems which finally allow for faster and more reliable solutions. It consists of an analytical inner optimisation loop to achieve a most profitable agricultural production for a given amount of water and an outer simulation-based optimisation loop to find the optimal groundwater abstraction pattern. Thereby, the behaviour of farms is described by crop-water-production functions and the aquifer response, including the seawater interface, is simulated by an artificial neural network. The methodology is applied exemplarily for the south Batinah re-gion/Oman, which is affected by saltwater intrusion into a coastal aquifer system due to excessive groundwater withdrawal for irrigated agriculture. Due to contradicting objectives like profit-oriented agriculture vs aquifer sustainability, a multi-objective optimisation is performed which can provide sustainable solutions for water and agricultural management over long-term periods at farm and regional scales in respect of water resources, environment, and socio-economic development.

Photonic simulation of entanglement growth and engineering after a spin chain quench.

PubMed

Pitsios, Ioannis; Banchi, Leonardo; Rab, Adil S; Bentivegna, Marco; Caprara, Debora; Crespi, Andrea; Spagnolo, Nicolò; Bose, Sougato; Mataloni, Paolo; Osellame, Roberto; Sciarrino, Fabio

2017-11-17

The time evolution of quantum many-body systems is one of the most important processes for benchmarking quantum simulators. The most curious feature of such dynamics is the growth of quantum entanglement to an amount proportional to the system size (volume law) even when interactions are local. This phenomenon has great ramifications for fundamental aspects, while its optimisation clearly has an impact on technology (e.g., for on-chip quantum networking). Here we use an integrated photonic chip with a circuit-based approach to simulate the dynamics of a spin chain and maximise the entanglement generation. The resulting entanglement is certified by constructing a second chip, which measures the entanglement between multiple distant pairs of simulated spins, as well as the block entanglement entropy. This is the first photonic simulation and optimisation of the extensive growth of entanglement in a spin chain, and opens up the use of photonic circuits for optimising quantum devices.

Airfoil Shape Optimization based on Surrogate Model

NASA Astrophysics Data System (ADS)

Mukesh, R.; Lingadurai, K.; Selvakumar, U.

2018-02-01

Engineering design problems always require enormous amount of real-time experiments and computational simulations in order to assess and ensure the design objectives of the problems subject to various constraints. In most of the cases, the computational resources and time required per simulation are large. In certain cases like sensitivity analysis, design optimisation etc where thousands and millions of simulations have to be carried out, it leads to have a life time of difficulty for designers. Nowadays approximation models, otherwise called as surrogate models (SM), are more widely employed in order to reduce the requirement of computational resources and time in analysing various engineering systems. Various approaches such as Kriging, neural networks, polynomials, Gaussian processes etc are used to construct the approximation models. The primary intention of this work is to employ the k-fold cross validation approach to study and evaluate the influence of various theoretical variogram models on the accuracy of the surrogate model construction. Ordinary Kriging and design of experiments (DOE) approaches are used to construct the SMs by approximating panel and viscous solution algorithms which are primarily used to solve the flow around airfoils and aircraft wings. The method of coupling the SMs with a suitable optimisation scheme to carryout an aerodynamic design optimisation process for airfoil shapes is also discussed.

Mutual information-based LPI optimisation for radar network

NASA Astrophysics Data System (ADS)

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.

Design Optimisation of a Magnetic Field Based Soft Tactile Sensor

PubMed Central

Raske, Nicholas; Kow, Junwai; Alazmani, Ali; Ghajari, Mazdak; Culmer, Peter; Hewson, Robert

2017-01-01

This paper investigates the design optimisation of a magnetic field based soft tactile sensor, comprised of a magnet and Hall effect module separated by an elastomer. The aim was to minimise sensitivity of the output force with respect to the input magnetic field; this was achieved by varying the geometry and material properties. Finite element simulations determined the magnetic field and structural behaviour under load. Genetic programming produced phenomenological expressions describing these responses. Optimisation studies constrained by a measurable force and stable loading conditions were conducted; these produced Pareto sets of designs from which the optimal sensor characteristics were selected. The optimisation demonstrated a compromise between sensitivity and the measurable force, a fabricated version of the optimised sensor validated the improvements made using this methodology. The approach presented can be applied in general for optimising soft tactile sensor designs over a range of applications and sensing modes. PMID:29099787

Thermal energy and economic analysis of a PCM-enhanced household envelope considering different climate zones in Morocco

NASA Astrophysics Data System (ADS)

Kharbouch, Yassine; Mimet, Abdelaziz; El Ganaoui, Mohammed; Ouhsaine, Lahoucine

2018-07-01

This study investigates the thermal energy potentials and economic feasibility of an air-conditioned family household-integrated phase change material (PCM) considering different climate zones in Morocco. A simulation-based optimisation was carried out in order to define the optimal design of a PCM-enhanced household envelope for thermal energy effectiveness and cost-effectiveness of predefined candidate solutions. The optimisation methodology is based on coupling Energyplus® as a dynamic simulation tool and GenOpt® as an optimisation tool. Considering the obtained optimum design strategies, a thermal energy and economic analysis are carried out to investigate PCMs' integration feasibility in the Moroccan constructions. The results show that the PCM-integrated household envelope allows minimising the cooling/heating thermal energy demand vs. a reference household without PCM. While for the cost-effectiveness optimisation, it has been deduced that the economic feasibility is stilling insufficient under the actual PCM market conditions. The optimal design parameters results are also analysed.

Optimisation of lateral car dynamics taking into account parameter uncertainties

NASA Astrophysics Data System (ADS)

Busch, Jochen; Bestle, Dieter

2014-02-01

Simulation studies on an active all-wheel-steering car show that disturbance of vehicle parameters have high influence on lateral car dynamics. This motivates the need of robust design against such parameter uncertainties. A specific parametrisation is established combining deterministic, velocity-dependent steering control parameters with partly uncertain, velocity-independent vehicle parameters for simultaneous use in a numerical optimisation process. Model-based objectives are formulated and summarised in a multi-objective optimisation problem where especially the lateral steady-state behaviour is improved by an adaption strategy based on measurable uncertainties. The normally distributed uncertainties are generated by optimal Latin hypercube sampling and a response surface based strategy helps to cut down time consuming model evaluations which offers the possibility to use a genetic optimisation algorithm. Optimisation results are discussed in different criterion spaces and the achieved improvements confirm the validity of the proposed procedure.

Optimisation study of a vehicle bumper subsystem with fuzzy parameters

NASA Astrophysics Data System (ADS)

Farkas, L.; Moens, D.; Donders, S.; Vandepitte, D.

2012-10-01

This paper deals with the design and optimisation for crashworthiness of a vehicle bumper subsystem, which is a key scenario for vehicle component design. The automotive manufacturers and suppliers have to find optimal design solutions for such subsystems that comply with the conflicting requirements of the regulatory bodies regarding functional performance (safety and repairability) and regarding the environmental impact (mass). For the bumper design challenge, an integrated methodology for multi-attribute design engineering of mechanical structures is set up. The integrated process captures the various tasks that are usually performed manually, this way facilitating the automated design iterations for optimisation. Subsequently, an optimisation process is applied that takes the effect of parametric uncertainties into account, such that the system level of failure possibility is acceptable. This optimisation process is referred to as possibility-based design optimisation and integrates the fuzzy FE analysis applied for the uncertainty treatment in crash simulations. This process is the counterpart of the reliability-based design optimisation used in a probabilistic context with statistically defined parameters (variabilities).

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

NASA Astrophysics Data System (ADS)

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.

Automatic optimisation of gamma dose rate sensor networks: The DETECT Optimisation Tool

NASA Astrophysics Data System (ADS)

Helle, K. B.; Müller, T. O.; Astrup, P.; Dyve, J. E.

2014-05-01

Fast delivery of comprehensive information on the radiological situation is essential for decision-making in nuclear emergencies. Most national radiological agencies in Europe employ gamma dose rate sensor networks to monitor radioactive pollution of the atmosphere. Sensor locations were often chosen using regular grids or according to administrative constraints. Nowadays, however, the choice can be based on more realistic risk assessment, as it is possible to simulate potential radioactive plumes. To support sensor planning, we developed the DETECT Optimisation Tool (DOT) within the scope of the EU FP 7 project DETECT. It evaluates the gamma dose rates that a proposed set of sensors might measure in an emergency and uses this information to optimise the sensor locations. The gamma dose rates are taken from a comprehensive library of simulations of atmospheric radioactive plumes from 64 source locations. These simulations cover the whole European Union, so the DOT allows evaluation and optimisation of sensor networks for all EU countries, as well as evaluation of fencing sensors around possible sources. Users can choose from seven cost functions to evaluate the capability of a given monitoring network for early detection of radioactive plumes or for the creation of dose maps. The DOT is implemented as a stand-alone easy-to-use JAVA-based application with a graphical user interface and an R backend. Users can run evaluations and optimisations, and display, store and download the results. The DOT runs on a server and can be accessed via common web browsers; it can also be installed locally.

Multidisciplinary design optimisation of a recurve bow based on applications of the autogenetic design theory and distributed computing

NASA Astrophysics Data System (ADS)

Fritzsche, Matthias; Kittel, Konstantin; Blankenburg, Alexander; Vajna, Sándor

2012-08-01

The focus of this paper is to present a method of multidisciplinary design optimisation based on the autogenetic design theory (ADT) that provides methods, which are partially implemented in the optimisation software described here. The main thesis of the ADT is that biological evolution and the process of developing products are mainly similar, i.e. procedures from biological evolution can be transferred into product development. In order to fulfil requirements and boundary conditions of any kind (that may change at any time), both biological evolution and product development look for appropriate solution possibilities in a certain area, and try to optimise those that are actually promising by varying parameters and combinations of these solutions. As the time necessary for multidisciplinary design optimisations is a critical aspect in product development, ways to distribute the optimisation process with the effective use of unused calculating capacity, can reduce the optimisation time drastically. Finally, a practical example shows how ADT methods and distributed optimising are applied to improve a product.

Advanced treatment planning using direct 4D optimisation for pencil-beam scanned particle therapy

NASA Astrophysics Data System (ADS)

Bernatowicz, Kinga; Zhang, Ye; Perrin, Rosalind; Weber, Damien C.; Lomax, Antony J.

2017-08-01

We report on development of a new four-dimensional (4D) optimisation approach for scanned proton beams, which incorporates both irregular motion patterns and the delivery dynamics of the treatment machine into the plan optimiser. Furthermore, we assess the effectiveness of this technique to reduce dose to critical structures in proximity to moving targets, while maintaining effective target dose homogeneity and coverage. The proposed approach has been tested using both a simulated phantom and a clinical liver cancer case, and allows for realistic 4D calculations and optimisation using irregular breathing patterns extracted from e.g. 4DCT-MRI (4D computed tomography-magnetic resonance imaging). 4D dose distributions resulting from our 4D optimisation can achieve almost the same quality as static plans, independent of the studied geometry/anatomy or selected motion (regular and irregular). Additionally, current implementation of the 4D optimisation approach requires less than 3 min to find the solution for a single field planned on 4DCT of a liver cancer patient. Although 4D optimisation allows for realistic calculations using irregular breathing patterns, it is very sensitive to variations from the planned motion. Based on a sensitivity analysis, target dose homogeneity comparable to static plans (D5-D95  <5%) has been found only for differences in amplitude of up to 1 mm, for changes in respiratory phase  <200 ms and for changes in the breathing period of  <20 ms in comparison to the motions used during optimisation. As such, methods to robustly deliver 4D optimised plans employing 4D intensity-modulated delivery are discussed.

Design optimisation of a TOF-based collimated camera prototype for online hadrontherapy monitoring

NASA Astrophysics Data System (ADS)

Pinto, M.; Dauvergne, D.; Freud, N.; Krimmer, J.; Letang, J. M.; Ray, C.; Roellinghoff, F.; Testa, E.

2014-12-01

Hadrontherapy is an innovative radiation therapy modality for which one of the main key advantages is the target conformality allowed by the physical properties of ion species. However, in order to maximise the exploitation of its potentialities, online monitoring is required in order to assert the treatment quality, namely monitoring devices relying on the detection of secondary radiations. Herein is presented a method based on Monte Carlo simulations to optimise a multi-slit collimated camera employing time-of-flight selection of prompt-gamma rays to be used in a clinical scenario. In addition, an analytical tool is developed based on the Monte Carlo data to predict the expected precision for a given geometrical configuration. Such a method follows the clinical workflow requirements to simultaneously have a solution that is relatively accurate and fast. Two different camera designs are proposed, considering different endpoints based on the trade-off between camera detection efficiency and spatial resolution to be used in a proton therapy treatment with active dose delivery and assuming a homogeneous target.

An illustration of new methods in machine condition monitoring, Part I: stochastic resonance

NASA Astrophysics Data System (ADS)

Worden, K.; Antoniadou, I.; Marchesiello, S.; Mba, C.; Garibaldi, L.

2017-05-01

There have been many recent developments in the application of data-based methods to machine condition monitoring. A powerful methodology based on machine learning has emerged, where diagnostics are based on a two-step procedure: extraction of damage-sensitive features, followed by unsupervised learning (novelty detection) or supervised learning (classification). The objective of the current pair of papers is simply to illustrate one state-of-the-art procedure for each step, using synthetic data representative of reality in terms of size and complexity. The first paper in the pair will deal with feature extraction. Although some papers have appeared in the recent past considering stochastic resonance as a means of amplifying damage information in signals, they have largely relied on ad hoc specifications of the resonator used. In contrast, the current paper will adopt a principled optimisation-based approach to the resonator design. The paper will also show that a discrete dynamical system can provide all the benefits of a continuous system, but also provide a considerable speed-up in terms of simulation time in order to facilitate the optimisation approach.

Distributed optimisation problem with communication delay and external disturbance

NASA Astrophysics Data System (ADS)

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.

Optimisation of quantitative lung SPECT applied to mild COPD: a software phantom simulation study.

PubMed

Norberg, Pernilla; Olsson, Anna; Alm Carlsson, Gudrun; Sandborg, Michael; Gustafsson, Agnetha

2015-01-01

The amount of inhomogeneities in a (99m)Tc Technegas single-photon emission computed tomography (SPECT) lung image, caused by reduced ventilation in lung regions affected by chronic obstructive pulmonary disease (COPD), is correlated to disease advancement. A quantitative analysis method, the CVT method, measuring these inhomogeneities was proposed in earlier work. To detect mild COPD, which is a difficult task, optimised parameter values are needed. In this work, the CVT method was optimised with respect to the parameter values of acquisition, reconstruction and analysis. The ordered subset expectation maximisation (OSEM) algorithm was used for reconstructing the lung SPECT images. As a first step towards clinical application of the CVT method in detecting mild COPD, this study was based on simulated SPECT images of an advanced anthropomorphic lung software phantom including respiratory and cardiac motion, where the mild COPD lung had an overall ventilation reduction of 5%. The best separation between healthy and mild COPD lung images as determined using the CVT measure of ventilation inhomogeneity and 125 MBq (99m)Tc was obtained using a low-energy high-resolution collimator (LEHR) and a power 6 Butterworth post-filter with a cutoff frequency of 0.6 to 0.7 cm(-1). Sixty-four reconstruction updates and a small kernel size should be used when the whole lung is analysed, and for the reduced lung a greater number of updates and a larger kernel size are needed. A LEHR collimator and 125 (99m)Tc MBq together with an optimal combination of cutoff frequency, number of updates and kernel size, gave the best result. Suboptimal selections of either cutoff frequency, number of updates and kernel size will reduce the imaging system's ability to detect mild COPD in the lung phantom.

Optimised collision avoidance for an ultra-close rendezvous with a failed satellite based on the Gauss pseudospectral method

NASA Astrophysics Data System (ADS)

Chu, Xiaoyu; Zhang, Jingrui; Lu, Shan; Zhang, Yao; Sun, Yue

2016-11-01

This paper presents a trajectory planning algorithm to optimise the collision avoidance of a chasing spacecraft operating in an ultra-close proximity to a failed satellite. The complex configuration and the tumbling motion of the failed satellite are considered. The two-spacecraft rendezvous dynamics are formulated based on the target body frame, and the collision avoidance constraints are detailed, particularly concerning the uncertainties. An optimisation solution of the approaching problem is generated using the Gauss pseudospectral method. A closed-loop control is used to track the optimised trajectory. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms.

Optimisation of the hybrid renewable energy system by HOMER, PSO and CPSO for the study area

NASA Astrophysics Data System (ADS)

Khare, Vikas; Nema, Savita; Baredar, Prashant

2017-04-01

This study is based on simulation and optimisation of the renewable energy system of the police control room at Sagar in central India. To analyse this hybrid system, the meteorological data of solar insolation and hourly wind speeds of Sagar in central India (longitude 78°45‧ and latitude 23°50‧) have been considered. The pattern of load consumption is studied and suitably modelled for optimisation of the hybrid energy system using HOMER software. The results are compared with those of the particle swarm optimisation and the chaotic particle swarm optimisation algorithms. The use of these two algorithms to optimise the hybrid system leads to a higher quality result with faster convergence. Based on the optimisation result, it has been found that replacing conventional energy sources by the solar-wind hybrid renewable energy system will be a feasible solution for the distribution of electric power as a stand-alone application at the police control room. This system is more environmentally friendly than the conventional diesel generator. The fuel cost reduction is approximately 70-80% more than that of the conventional diesel generator.

Identification of the contribution of contact and aerial biomechanical parameters in acrobatic performance

PubMed Central

Haering, Diane; Huchez, Aurore; Barbier, Franck; Holvoët, Patrice; Begon, Mickaël

2017-01-01

Introduction Teaching acrobatic skills with a minimal amount of repetition is a major challenge for coaches. Biomechanical, statistical or computer simulation tools can help them identify the most determinant factors of performance. Release parameters, change in moment of inertia and segmental momentum transfers were identified in the prediction of acrobatics success. The purpose of the present study was to evaluate the relative contribution of these parameters in performance throughout expertise or optimisation based improvements. The counter movement forward in flight (CMFIF) was chosen for its intrinsic dichotomy between the accessibility of its attempt and complexity of its mastery. Methods Three repetitions of the CMFIF performed by eight novice and eight advanced female gymnasts were recorded using a motion capture system. Optimal aerial techniques that maximise rotation potential at regrasp were also computed. A 14-segment-multibody-model defined through the Rigid Body Dynamics Library was used to compute recorded and optimal kinematics, and biomechanical parameters. A stepwise multiple linear regression was used to determine the relative contribution of these parameters in novice recorded, novice optimised, advanced recorded and advanced optimised trials. Finally, fixed effects of expertise and optimisation were tested through a mixed-effects analysis. Results and discussion Variation in release state only contributed to performances in novice recorded trials. Moment of inertia contribution to performance increased from novice recorded, to novice optimised, advanced recorded, and advanced optimised trials. Contribution to performance of momentum transfer to the trunk during the flight prevailed in all recorded trials. Although optimisation decreased transfer contribution, momentum transfer to the arms appeared. Conclusion Findings suggest that novices should be coached on both contact and aerial technique. Inversely, mainly improved aerial technique helped advanced gymnasts increase their performance. For both, reduction of the moment of inertia should be focused on. The method proposed in this article could be generalized to any aerial skill learning investigation. PMID:28422954

Optimisation of sensing time and transmission time in cognitive radio-based smart grid networks

NASA Astrophysics Data System (ADS)

Yang, Chao; Fu, Yuli; Yang, Junjie

2016-07-01

Cognitive radio (CR)-based smart grid (SG) networks have been widely recognised as emerging communication paradigms in power grids. However, a sufficient spectrum resource and reliability are two major challenges for real-time applications in CR-based SG networks. In this article, we study the traffic data collection problem. Based on the two-stage power pricing model, the power price is associated with the efficient received traffic data in a metre data management system (MDMS). In order to minimise the system power price, a wideband hybrid access strategy is proposed and analysed, to share the spectrum between the SG nodes and CR networks. The sensing time and transmission time are jointly optimised, while both the interference to primary users and the spectrum opportunity loss of secondary users are considered. Two algorithms are proposed to solve the joint optimisation problem. Simulation results show that the proposed joint optimisation algorithms outperform the fixed parameters (sensing time and transmission time) algorithms, and the power cost is reduced efficiently.

Distributed convex optimisation with event-triggered communication in networked systems

NASA Astrophysics Data System (ADS)

Liu, Jiayun; Chen, Weisheng

2016-12-01

This paper studies the distributed convex optimisation problem over directed networks. Motivated by practical considerations, we propose a novel distributed zero-gradient-sum optimisation algorithm with event-triggered communication. Therefore, communication and control updates just occur at discrete instants when some predefined condition satisfies. Thus, compared with the time-driven distributed optimisation algorithms, the proposed algorithm has the advantages of less energy consumption and less communication cost. Based on Lyapunov approaches, we show that the proposed algorithm makes the system states asymptotically converge to the solution of the problem exponentially fast and the Zeno behaviour is excluded. Finally, simulation example is given to illustrate the effectiveness of the proposed algorithm.

Population Fisher information matrix and optimal design of discrete data responses in population pharmacodynamic experiments.

PubMed

Ogungbenro, Kayode; Aarons, Leon

2011-08-01

In the recent years, interest in the application of experimental design theory to population pharmacokinetic (PK) and pharmacodynamic (PD) experiments has increased. The aim is to improve the efficiency and the precision with which parameters are estimated during data analysis and sometimes to increase the power and reduce the sample size required for hypothesis testing. The population Fisher information matrix (PFIM) has been described for uniresponse and multiresponse population PK experiments for design evaluation and optimisation. Despite these developments and availability of tools for optimal design of population PK and PD experiments much of the effort has been focused on repeated continuous variable measurements with less work being done on repeated discrete type measurements. Discrete data arise mainly in PDs e.g. ordinal, nominal, dichotomous or count measurements. This paper implements expressions for the PFIM for repeated ordinal, dichotomous and count measurements based on analysis by a mixed-effects modelling technique. Three simulation studies were used to investigate the performance of the expressions. Example 1 is based on repeated dichotomous measurements, Example 2 is based on repeated count measurements and Example 3 is based on repeated ordinal measurements. Data simulated in MATLAB were analysed using NONMEM (Laplace method) and the glmmML package in R (Laplace and adaptive Gauss-Hermite quadrature methods). The results obtained for Examples 1 and 2 showed good agreement between the relative standard errors obtained using the PFIM and simulations. The results obtained for Example 3 showed the importance of sampling at the most informative time points. Implementation of these expressions will provide the opportunity for efficient design of population PD experiments that involve discrete type data through design evaluation and optimisation.

Optimisation in radiotherapy. III: Stochastic optimisation algorithms and conclusions.

PubMed

Ebert, M

1997-12-01

This is the final article in a three part examination of optimisation in radiotherapy. Previous articles have established the bases and form of the radiotherapy optimisation problem, and examined certain types of optimisation algorithm, namely, those which perform some form of ordered search of the solution space (mathematical programming), and those which attempt to find the closest feasible solution to the inverse planning problem (deterministic inversion). The current paper examines algorithms which search the space of possible irradiation strategies by stochastic methods. The resulting iterative search methods move about the solution space by sampling random variates, which gradually become more constricted as the algorithm converges upon the optimal solution. This paper also discusses the implementation of optimisation in radiotherapy practice.

On the performance of energy detection-based CR with SC diversity over IG channel

NASA Astrophysics Data System (ADS)

Verma, Pappu Kumar; Soni, Sanjay Kumar; Jain, Priyanka

2017-12-01

Cognitive radio (CR) is a viable 5G technology to address the scarcity of the spectrum. Energy detection-based sensing is known to be the simplest method as far as hardware complexity is concerned. In this paper, the performance of spectrum sensing-based energy detection technique in CR networks over inverse Gaussian channel for selection combining diversity technique is analysed. More specifically, accurate analytical expressions for the average detection probability under different detection scenarios such as single channel (no diversity) and with diversity reception are derived and evaluated. Further, the detection threshold parameter is optimised by minimising the probability of error over several diversity branches. The results clearly show the significant improvement in the probability of detection when optimised threshold parameter is applied. The impact of shadowing parameters on the performance of energy detector is studied in terms of complimentary receiver operating characteristic curve. To verify the correctness of our analysis, the derived analytical expressions are corroborated via exact result and Monte Carlo simulations.

A simulation-optimization model for effective water resources management in the coastal zone

NASA Astrophysics Data System (ADS)

Spanoudaki, Katerina; Kampanis, Nikolaos

2015-04-01

Coastal areas are the most densely-populated areas in the world. Consequently water demand is high, posing great pressure on fresh water resources. Climatic change and its direct impacts on meteorological variables (e.g. precipitation) and indirect impact on sea level rise, as well as anthropogenic pressures (e.g. groundwater abstraction), are strong drivers causing groundwater salinisation and subsequently affecting coastal wetlands salinity with adverse effects on the corresponding ecosystems. Coastal zones are a difficult hydrologic environment to represent with a mathematical model due to the large number of contributing hydrologic processes and variable-density flow conditions. Simulation of sea level rise and tidal effects on aquifer salinisation and accurate prediction of interactions between coastal waters, groundwater and neighbouring wetlands requires the use of integrated surface water-groundwater mathematical models. In the past few decades several computer codes have been developed to simulate coupled surface and groundwater flow. However, most integrated surface water-groundwater models are based on the assumption of constant fluid density and therefore their applicability to coastal regions is questionable. Thus, most of the existing codes are not well-suited to represent surface water-groundwater interactions in coastal areas. To this end, the 3D integrated surface water-groundwater model IRENE (Spanoudaki et al., 2009; Spanoudaki, 2010) has been modified in order to simulate surface water-groundwater flow and salinity interactions in the coastal zone. IRENE, in its original form, couples the 3D shallow water equations to the equations describing 3D saturated groundwater flow of constant density. A semi-implicit finite difference scheme is used to solve the surface water flow equations, while a fully implicit finite difference scheme is used for the groundwater equations. Pollution interactions are simulated by coupling the advection-diffusion equation describing the fate and transport of contaminants introduced in a 3D turbulent flow field to the partial differential equation describing the fate and transport of contaminants in 3D transient groundwater flow systems. The model has been further developed to include the effects of density variations on surface water and groundwater flow, while the already built-in solute transport capabilities are used to simulate salinity interactions. The refined model is based on the finite volume method using a cell-centred structured grid, providing thus flexibility and accuracy in simulating irregular boundary geometries. For addressing water resources management problems, simulation models are usually externally coupled with optimisation-based management models. However this usually requires a very large number of iterations between the optimisation and simulation models in order to obtain the optimal management solution. As an alternative approach, for improved computational efficiency, an Artificial Neural Network (ANN) is trained as an approximate simulator of IRENE. The trained ANN is then linked to a Genetic Algorithm (GA) based optimisation model for managing salinisation problems in the coastal zone. The linked simulation-optimisation model is applied to a hypothetical study area for performance evaluation. Acknowledgement The work presented in this paper has been funded by the Greek State Scholarships Foundation (IKY), Fellowships of Excellence for Postdoctoral Studies (Siemens Program), 'A simulation-optimization model for assessing the best practices for the protection of surface water and groundwater in the coastal zone', (2013 - 2015). References Spanoudaki, K., Stamou, A.I. and Nanou-Giannarou, A. (2009). Development and verification of a 3-D integrated surface water-groundwater model. Journal of Hydrology, 375 (3-4), 410-427. Spanoudaki, K. (2010). Integrated numerical modelling of surface water groundwater systems (in Greek). Ph.D. Thesis, National Technical University of Athens, Greece.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kieselmann, J; Bartzsch, S; Oelfke, U

Purpose: Microbeam Radiation Therapy is a preclinical method in radiation oncology that modulates radiation fields on a micrometre scale. Dose calculation is challenging due to arising dose gradients and therapeutically important dose ranges. Monte Carlo (MC) simulations, often used as gold standard, are computationally expensive and hence too slow for the optimisation of treatment parameters in future clinical applications. On the other hand, conventional kernel based dose calculation leads to inaccurate results close to material interfaces. The purpose of this work is to overcome these inaccuracies while keeping computation times low. Methods: A point kernel superposition algorithm is modified tomore » account for tissue inhomogeneities. Instead of conventional ray tracing approaches, methods from differential geometry are applied and the space around the primary photon interaction is locally warped. The performance of this approach is compared to MC simulations and a simple convolution algorithm (CA) for two different phantoms and photon spectra. Results: While peak doses of all dose calculation methods agreed within less than 4% deviations, the proposed approach surpassed a simple convolution algorithm in accuracy by a factor of up to 3 in the scatter dose. In a treatment geometry similar to possible future clinical situations differences between Monte Carlo and the differential geometry algorithm were less than 3%. At the same time the calculation time did not exceed 15 minutes. Conclusion: With the developed method it was possible to improve the dose calculation based on the CA method with respect to accuracy especially at sharp tissue boundaries. While the calculation is more extensive than for the CA method and depends on field size, the typical calculation time for a 20×20 mm{sup 2} field on a 3.4 GHz and 8 GByte RAM processor remained below 15 minutes. Parallelisation and optimisation of the algorithm could lead to further significant calculation time reductions.« less

Global optimisation methods for poroelastic material characterisation using a clamped sample in a Kundt tube setup

NASA Astrophysics Data System (ADS)

Vanhuyse, Johan; Deckers, Elke; Jonckheere, Stijn; Pluymers, Bert; Desmet, Wim

2016-02-01

The Biot theory is commonly used for the simulation of the vibro-acoustic behaviour of poroelastic materials. However, it relies on a number of material parameters. These can be hard to characterize and require dedicated measurement setups, yielding a time-consuming and costly characterisation. This paper presents a characterisation method which is able to identify all material parameters using only an impedance tube. The method relies on the assumption that the sample is clamped within the tube, that the shear wave is excited and that the acoustic field is no longer one-dimensional. This paper numerically shows the potential of the developed method. It therefore performs a sensitivity analysis of the quantification parameters, i.e. reflection coefficients and relative pressures, and a parameter estimation using global optimisation methods. A 3-step procedure is developed and validated. It is shown that even in the presence of numerically simulated noise this procedure leads to a robust parameter estimation.

Floating-to-Fixed-Point Conversion for Digital Signal Processors

NASA Astrophysics Data System (ADS)

Menard, Daniel; Chillet, Daniel; Sentieys, Olivier

2006-12-01

Digital signal processing applications are specified with floating-point data types but they are usually implemented in embedded systems with fixed-point arithmetic to minimise cost and power consumption. Thus, methodologies which establish automatically the fixed-point specification are required to reduce the application time-to-market. In this paper, a new methodology for the floating-to-fixed point conversion is proposed for software implementations. The aim of our approach is to determine the fixed-point specification which minimises the code execution time for a given accuracy constraint. Compared to previous methodologies, our approach takes into account the DSP architecture to optimise the fixed-point formats and the floating-to-fixed-point conversion process is coupled with the code generation process. The fixed-point data types and the position of the scaling operations are optimised to reduce the code execution time. To evaluate the fixed-point computation accuracy, an analytical approach is used to reduce the optimisation time compared to the existing methods based on simulation. The methodology stages are described and several experiment results are presented to underline the efficiency of this approach.

Coil optimisation for transcranial magnetic stimulation in realistic head geometry.

PubMed

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.

Using modified fruit fly optimisation algorithm to perform the function test and case studies

NASA Astrophysics Data System (ADS)

Pan, Wen-Tsao

2013-06-01

Evolutionary computation is a computing mode established by practically simulating natural evolutionary processes based on the concept of Darwinian Theory, and it is a common research method. The main contribution of this paper was to reinforce the function of searching for the optimised solution using the fruit fly optimization algorithm (FOA), in order to avoid the acquisition of local extremum solutions. The evolutionary computation has grown to include the concepts of animal foraging behaviour and group behaviour. This study discussed three common evolutionary computation methods and compared them with the modified fruit fly optimization algorithm (MFOA). It further investigated the ability of the three mathematical functions in computing extreme values, as well as the algorithm execution speed and the forecast ability of the forecasting model built using the optimised general regression neural network (GRNN) parameters. The findings indicated that there was no obvious difference between particle swarm optimization and the MFOA in regards to the ability to compute extreme values; however, they were both better than the artificial fish swarm algorithm and FOA. In addition, the MFOA performed better than the particle swarm optimization in regards to the algorithm execution speed, and the forecast ability of the forecasting model built using the MFOA's GRNN parameters was better than that of the other three forecasting models.

Comparison of simulation and experimental results for a gas puff nozzle on Ambiorix

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnier, J-N.; Chevalier, J-M.; Dubroca, B.

One of source term of Z-Pinch experiments is the gas puff density profile. In order to characterize the gas jet, an experiment based on interferometry has been performed. The first study was a point measurement (a section density profile) which led us to develop a global and instantaneous interferometry imaging method. In order to optimise the nozzle, we simulated the experiment with a flow calculation code (ARES). In this paper, the experimental results are compared with simulations. The different gas properties (He, Ne, Ar) and the flow duration lead us to take care, on the one hand, of the gasmore » viscosity, and on the other, of modifying the code for an instationary flow.« less

Design and experimental validation of linear and nonlinear vehicle steering control strategies

NASA Astrophysics Data System (ADS)

Menhour, Lghani; Lechner, Daniel; Charara, Ali

2012-06-01

This paper proposes the design of three control laws dedicated to vehicle steering control, two based on robust linear control strategies and one based on nonlinear control strategies, and presents a comparison between them. The two robust linear control laws (indirect and direct methods) are built around M linear bicycle models, each of these control laws is composed of two M proportional integral derivative (PID) controllers: one M PID controller to control the lateral deviation and the other M PID controller to control the vehicle yaw angle. The indirect control law method is designed using an oscillation method and a nonlinear optimisation subject to H ∞ constraint. The direct control law method is designed using a linear matrix inequality optimisation in order to achieve H ∞ performances. The nonlinear control method used for the correction of the lateral deviation is based on a continuous first-order sliding-mode controller. The different methods are designed using a linear bicycle vehicle model with variant parameters, but the aim is to simulate the nonlinear vehicle behaviour under high dynamic demands with a four-wheel vehicle model. These steering vehicle controls are validated experimentally using the data acquired using a laboratory vehicle, Peugeot 307, developed by National Institute for Transport and Safety Research - Department of Accident Mechanism Analysis Laboratory's (INRETS-MA) and their performance results are compared. Moreover, an unknown input sliding-mode observer is introduced to estimate the road bank angle.

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

NASA Astrophysics Data System (ADS)

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.

Fast Simulation of the Impact Parameter Calculation of Electrons through Pair Production

NASA Astrophysics Data System (ADS)

Bang, Hyesun; Kweon, MinJung; Huh, Kyoung Bum; Pachmayer, Yvonne

2018-05-01

A fast simulation method is introduced that reduces tremendously the time required for the impact parameter calculation, a key observable in physics analyses of high energy physics experiments and detector optimisation studies. The impact parameter of electrons produced through pair production was calculated considering key related processes using the Bethe-Heitler formula, the Tsai formula and a simple geometric model. The calculations were performed at various conditions and the results were compared with those from full GEANT4 simulations. The computation time using this fast simulation method is 104 times shorter than that of the full GEANT4 simulation.

Multi-Optimisation Consensus Clustering

NASA Astrophysics Data System (ADS)

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.

Synthesis of concentric circular antenna arrays using dragonfly algorithm

NASA Astrophysics Data System (ADS)

Babayigit, B.

2018-05-01

Due to the strong non-linear relationship between the array factor and the array elements, concentric circular antenna array (CCAA) synthesis problem is challenging. Nature-inspired optimisation techniques have been playing an important role in solving array synthesis problems. Dragonfly algorithm (DA) is a novel nature-inspired optimisation technique which is based on the static and dynamic swarming behaviours of dragonflies in nature. This paper presents the design of CCAAs to get low sidelobes using DA. The effectiveness of the proposed DA is investigated in two different (with and without centre element) cases of two three-ring (having 4-, 6-, 8-element or 8-, 10-, 12-element) CCAA design. The radiation pattern of each design cases is obtained by finding optimal excitation weights of the array elements using DA. Simulation results show that the proposed algorithm outperforms the other state-of-the-art techniques (symbiotic organisms search, biogeography-based optimisation, sequential quadratic programming, opposition-based gravitational search algorithm, cat swarm optimisation, firefly algorithm, evolutionary programming) for all design cases. DA can be a promising technique for electromagnetic problems.

VLSI Technology for Cognitive Radio

NASA Astrophysics Data System (ADS)

VIJAYALAKSHMI, B.; SIDDAIAH, P.

2017-08-01

One of the most challenging tasks of cognitive radio is the efficiency in the spectrum sensing scheme to overcome the spectrum scarcity problem. The popular and widely used spectrum sensing technique is the energy detection scheme as it is very simple and doesn’t require any previous information related to the signal. We propose one such approach which is an optimised spectrum sensing scheme with reduced filter structure. The optimisation is done in terms of area and power performance of the spectrum. The simulations of the VLSI structure of the optimised flexible spectrum is done using verilog coding by using the XILINX ISE software. Our method produces performance with 13% reduction in area and 66% reduction in power consumption in comparison to the flexible spectrum sensing scheme. All the results are tabulated and comparisons are made. A new scheme for optimised and effective spectrum sensing opens up with our model.

A domain specific language for performance portable molecular dynamics algorithms

NASA Astrophysics Data System (ADS)

Saunders, William Robert; Grant, James; Müller, Eike Hermann

2018-03-01

Developers of Molecular Dynamics (MD) codes face significant challenges when adapting existing simulation packages to new hardware. In a continuously diversifying hardware landscape it becomes increasingly difficult for scientists to be experts both in their own domain (physics/chemistry/biology) and specialists in the low level parallelisation and optimisation of their codes. To address this challenge, we describe a "Separation of Concerns" approach for the development of parallel and optimised MD codes: the science specialist writes code at a high abstraction level in a domain specific language (DSL), which is then translated into efficient computer code by a scientific programmer. In a related context, an abstraction for the solution of partial differential equations with grid based methods has recently been implemented in the (Py)OP2 library. Inspired by this approach, we develop a Python code generation system for molecular dynamics simulations on different parallel architectures, including massively parallel distributed memory systems and GPUs. We demonstrate the efficiency of the auto-generated code by studying its performance and scalability on different hardware and compare it to other state-of-the-art simulation packages. With growing data volumes the extraction of physically meaningful information from the simulation becomes increasingly challenging and requires equally efficient implementations. A particular advantage of our approach is the easy expression of such analysis algorithms. We consider two popular methods for deducing the crystalline structure of a material from the local environment of each atom, show how they can be expressed in our abstraction and implement them in the code generation framework.

Influence of the Size of Cohorts in Adaptive Design for Nonlinear Mixed Effects Models: An Evaluation by Simulation for a Pharmacokinetic and Pharmacodynamic Model for a Biomarker in Oncology

PubMed Central

Lestini, Giulia; Dumont, Cyrielle; Mentré, France

2015-01-01

Purpose In this study we aimed to evaluate adaptive designs (ADs) by clinical trial simulation for a pharmacokinetic-pharmacodynamic model in oncology and to compare them with one-stage designs, i.e. when no adaptation is performed, using wrong prior parameters. Methods We evaluated two one-stage designs, ξ0 and ξ*, optimised for prior and true population parameters, Ψ0 and Ψ*, and several ADs (two-, three- and five-stage). All designs had 50 patients. For ADs, the first cohort design was ξ0. The next cohort design was optimised using prior information updated from the previous cohort. Optimal design was based on the determinant of the Fisher information matrix using PFIM. Design evaluation was performed by clinical trial simulations using data simulated from Ψ*. Results Estimation results of two-stage ADs and ξ* were close and much better than those obtained with ξ0. The balanced two-stage AD performed better than two-stage ADs with different cohort sizes. Three-and five-stage ADs were better than two-stage with small first cohort, but not better than the balanced two-stage design. Conclusions Two-stage ADs are useful when prior parameters are unreliable. In case of small first cohort, more adaptations are needed but these designs are complex to implement. PMID:26123680

Predictive Array Design. A method for sampling combinatorial chemistry library space.

PubMed

Lipkin, M J; Rose, V S; Wood, J

2002-01-01

A method, Predictive Array Design, is presented for sampling combinatorial chemistry space and selecting a subarray for synthesis based on the experimental design method of Latin Squares. The method is appropriate for libraries with three sites of variation. Libraries with four sites of variation can be designed using the Graeco-Latin Square. Simulated annealing is used to optimise the physicochemical property profile of the sub-array. The sub-array can be used to make predictions of the activity of compounds in the all combinations array if we assume each monomer has a relatively constant contribution to activity and that the activity of a compound is composed of the sum of the activities of its constitutive monomers.

Discrete bacteria foraging optimization algorithm for graph based problems - a transition from continuous to discrete

NASA Astrophysics Data System (ADS)

Sur, Chiranjib; Shukla, Anupam

2018-03-01

Bacteria Foraging Optimisation Algorithm is a collective behaviour-based meta-heuristics searching depending on the social influence of the bacteria co-agents in the search space of the problem. The algorithm faces tremendous hindrance in terms of its application for discrete problems and graph-based problems due to biased mathematical modelling and dynamic structure of the algorithm. This had been the key factor to revive and introduce the discrete form called Discrete Bacteria Foraging Optimisation (DBFO) Algorithm for discrete problems which exceeds the number of continuous domain problems represented by mathematical and numerical equations in real life. In this work, we have mainly simulated a graph-based road multi-objective optimisation problem and have discussed the prospect of its utilisation in other similar optimisation problems and graph-based problems. The various solution representations that can be handled by this DBFO has also been discussed. The implications and dynamics of the various parameters used in the DBFO are illustrated from the point view of the problems and has been a combination of both exploration and exploitation. The result of DBFO has been compared with Ant Colony Optimisation and Intelligent Water Drops Algorithms. Important features of DBFO are that the bacteria agents do not depend on the local heuristic information but estimates new exploration schemes depending upon the previous experience and covered path analysis. This makes the algorithm better in combination generation for graph-based problems and combination generation for NP hard problems.

Optimisation of SIW bandpass filter with wide and sharp stopband using space mapping

NASA Astrophysics Data System (ADS)

Xu, Juan; Bi, Jun Jian; Li, Zhao Long; Chen, Ru shan

2016-12-01

This work presents a substrate integrated waveguide (SIW) bandpass filter with wide and precipitous stopband, which is different from filters with a direct input/output coupling structure. Higher modes in the SIW cavities are used to generate the finite transmission zeros for improved stopband performance. The design of SIW filters requires full wave electromagnetic simulation and extensive optimisation. If a full wave solver is used for optimisation, the design process is very time consuming. The space mapping (SM) approach has been called upon to alleviate this problem. In this case, the coarse model is optimised using an equivalent circuit model-based representation of the structure for fast computations. On the other hand, the verification of the design is completed with an accurate fine model full wave simulation. A fourth-order filter with a passband of 12.0-12.5 GHz is fabricated on a single layer Rogers RT/Duroid 5880 substrate. The return loss is better than 17.4 dB in the passband and the rejection is more than 40 dB in the stopband. The stopband is from 2 to 11 GHz and 13.5 to 17.3 GHz, demonstrating a wide bandwidth performance.

Sybil--efficient constraint-based modelling in R.

PubMed

Gelius-Dietrich, Gabriel; Desouki, Abdelmoneim Amer; Fritzemeier, Claus Jonathan; Lercher, Martin J

2013-11-13

Constraint-based analyses of metabolic networks are widely used to simulate the properties of genome-scale metabolic networks. Publicly available implementations tend to be slow, impeding large scale analyses such as the genome-wide computation of pairwise gene knock-outs, or the automated search for model improvements. Furthermore, available implementations cannot easily be extended or adapted by users. Here, we present sybil, an open source software library for constraint-based analyses in R; R is a free, platform-independent environment for statistical computing and graphics that is widely used in bioinformatics. Among other functions, sybil currently provides efficient methods for flux-balance analysis (FBA), MOMA, and ROOM that are about ten times faster than previous implementations when calculating the effect of whole-genome single gene deletions in silico on a complete E. coli metabolic model. Due to the object-oriented architecture of sybil, users can easily build analysis pipelines in R or even implement their own constraint-based algorithms. Based on its highly efficient communication with different mathematical optimisation programs, sybil facilitates the exploration of high-dimensional optimisation problems on small time scales. Sybil and all its dependencies are open source. Sybil and its documentation are available for download from the comprehensive R archive network (CRAN).

Process Simulation of Aluminium Sheet Metal Deep Drawing at Elevated Temperatures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winklhofer, Johannes; Trattnig, Gernot; Lind, Christoph

Lightweight design is essential for an economic and environmentally friendly vehicle. Aluminium sheet metal is well known for its ability to improve the strength to weight ratio of lightweight structures. One disadvantage of aluminium is that it is less formable than steel. Therefore complex part geometries can only be realized by expensive multi-step production processes. One method for overcoming this disadvantage is deep drawing at elevated temperatures. In this way the formability of aluminium sheet metal can be improved significantly, and the number of necessary production steps can thereby be reduced. This paper introduces deep drawing of aluminium sheet metalmore » at elevated temperatures, a corresponding simulation method, a characteristic process and its optimization. The temperature and strain rate dependent material properties of a 5xxx series alloy and their modelling are discussed. A three dimensional thermomechanically coupled finite element deep drawing simulation model and its validation are presented. Based on the validated simulation model an optimised process strategy regarding formability, time and cost is introduced.« less

A novel swarm intelligence algorithm for finding DNA motifs.

PubMed

Lei, Chengwei; Ruan, Jianhua

2009-01-01

Discovering DNA motifs from co-expressed or co-regulated genes is an important step towards deciphering complex gene regulatory networks and understanding gene functions. Despite significant improvement in the last decade, it still remains one of the most challenging problems in computational molecular biology. In this work, we propose a novel motif finding algorithm that finds consensus patterns using a population-based stochastic optimisation technique called Particle Swarm Optimisation (PSO), which has been shown to be effective in optimising difficult multidimensional problems in continuous domains. We propose to use a word dissimilarity graph to remap the neighborhood structure of the solution space of DNA motifs, and propose a modification of the naive PSO algorithm to accommodate discrete variables. In order to improve efficiency, we also propose several strategies for escaping from local optima and for automatically determining the termination criteria. Experimental results on simulated challenge problems show that our method is both more efficient and more accurate than several existing algorithms. Applications to several sets of real promoter sequences also show that our approach is able to detect known transcription factor binding sites, and outperforms two of the most popular existing algorithms.

Application of the adjoint optimisation of shock control bump for ONERA-M6 wing

NASA Astrophysics Data System (ADS)

Nejati, A.; Mazaheri, K.

2017-11-01

This article is devoted to the numerical investigation of the shock wave/boundary layer interaction (SWBLI) as the main factor influencing the aerodynamic performance of transonic bumped airfoils and wings. The numerical analysis is conducted for the ONERA-M6 wing through a shock control bump (SCB) shape optimisation process using the adjoint optimisation method. SWBLI is analyzed for both clean and bumped airfoils and wings, and it is shown how the modified wave structure originating from upstream of the SCB reduces the wave drag, by improving the boundary layer velocity profile downstream of the shock wave. The numerical simulation of the turbulent viscous flow and a gradient-based adjoint algorithm are used to find the optimum location and shape of the SCB for the ONERA-M6 airfoil and wing. Two different geometrical models are introduced for the 3D SCB, one with linear variations, and another with periodic variations. Both configurations result in drag reduction and improvement in the aerodynamic efficiency, but the periodic model is more effective. Although the three-dimensional flow structure involves much more complexities, the overall results are shown to be similar to the two-dimensional case.

An improved design method based on polyphase components for digital FIR filters

NASA Astrophysics Data System (ADS)

Kumar, A.; Kuldeep, B.; Singh, G. K.; Lee, Heung No

2017-11-01

This paper presents an efficient design of digital finite impulse response (FIR) filter, based on polyphase components and swarm optimisation techniques (SOTs). For this purpose, the design problem is formulated as mean square error between the actual response and ideal response in frequency domain using polyphase components of a prototype filter. To achieve more precise frequency response at some specified frequency, fractional derivative constraints (FDCs) have been applied, and optimal FDCs are computed using SOTs such as cuckoo search and modified cuckoo search algorithms. A comparative study of well-proved swarm optimisation, called particle swarm optimisation and artificial bee colony algorithm is made. The excellence of proposed method is evaluated using several important attributes of a filter. Comparative study evidences the excellence of proposed method for effective design of FIR filter.

Employing multi-GPU power for molecular dynamics simulation: an extension of GALAMOST

NASA Astrophysics Data System (ADS)

Zhu, You-Liang; Pan, Deng; Li, Zhan-Wei; Liu, Hong; Qian, Hu-Jun; Zhao, Yang; Lu, Zhong-Yuan; Sun, Zhao-Yan

2018-04-01

We describe the algorithm of employing multi-GPU power on the basis of Message Passing Interface (MPI) domain decomposition in a molecular dynamics code, GALAMOST, which is designed for the coarse-grained simulation of soft matters. The code of multi-GPU version is developed based on our previous single-GPU version. In multi-GPU runs, one GPU takes charge of one domain and runs single-GPU code path. The communication between neighbouring domains takes a similar algorithm of CPU-based code of LAMMPS, but is optimised specifically for GPUs. We employ a memory-saving design which can enlarge maximum system size at the same device condition. An optimisation algorithm is employed to prolong the update period of neighbour list. We demonstrate good performance of multi-GPU runs on the simulation of Lennard-Jones liquid, dissipative particle dynamics liquid, polymer and nanoparticle composite, and two-patch particles on workstation. A good scaling of many nodes on cluster for two-patch particles is presented.

Unexpected finite size effects in interfacial systems: Why bigger is not always better—Increase in uncertainty of surface tension with bulk phase width

NASA Astrophysics Data System (ADS)

Longford, Francis G. J.; Essex, Jonathan W.; Skylaris, Chris-Kriton; Frey, Jeremy G.

2018-06-01

We present an unexpected finite size effect affecting interfacial molecular simulations that is proportional to the width-to-surface-area ratio of the bulk phase Ll/A. This finite size effect has a significant impact on the variance of surface tension values calculated using the virial summation method. A theoretical derivation of the origin of the effect is proposed, giving a new insight into the importance of optimising system dimensions in interfacial simulations. We demonstrate the consequences of this finite size effect via a new way to estimate the surface energetic and entropic properties of simulated air-liquid interfaces. Our method is based on macroscopic thermodynamic theory and involves comparing the internal energies of systems with varying dimensions. We present the testing of these methods using simulations of the TIP4P/2005 water forcefield and a Lennard-Jones fluid model of argon. Finally, we provide suggestions of additional situations, in which this finite size effect is expected to be significant, as well as possible ways to avoid its impact.

Fractionation of wastewater characteristics for modelling of Firle Sewage Treatment Works, Harare, Zimbabwe

NASA Astrophysics Data System (ADS)

Muserere, Simon Takawira; Hoko, Zvikomborero; Nhapi, Innocent

Varying conditions are required for different species of microorganisms for the complex biological processes taking place within the activated sludge treatment system. It is against the requirement to manage this complex dynamic system that computer simulators were developed to aid in optimising activated sludge treatment processes. These computer simulators require calibration with quality data input that include wastewater fractionation among others. Thus, this research fractionated raw sewage, at Firle Sewage Treatment Works (STW), for calibration of the BioWin simulation model. Firle STW is a 3-stage activated sludge system. Wastewater characteristics of importance for activated sludge process design can be grouped into carbonaceous, nitrogenous and phosphorus compounds. Division of the substrates and compounds into their constituent fractions is called fractionation and is a valuable tool for process assessment. Fractionation can be carried out using bioassay methods or much simpler physico-chemical methods. The bioassay methods require considerable experience with experimental activated sludge systems and associated measurement techniques while the physico-chemical methods are straight forward. Plant raw wastewater fractionation was carried out through two 14-day campaign periods, the first being from 3 to 16 July 2013 and the second was from 1 to 14 October 2013. According to the Zimbabwean Environmental Management Act, and based on the sensitivity of its catchment, Firle STW effluent discharge regulatory standards in mg/L are COD (<60), TN (<10), ammonia (<0.2), and TP (<1). On the other hand Firle STW Unit 4 effluent quality results based on City of Harare records in mg/L during the period of study were COD (90 ± 35), TN (9.0 ± 3.0), ammonia (0.2 ± 0.4) and TP (3.0 ± 1.0). The raw sewage parameter concentrations measured during the study in mg/L and fractions for raw sewage respectively were as follows total COD (680 ± 37), slowly biodegradable COD (456 ± 23), (0.7), readily biodegradable COD (131 ± 11), (0.2), soluble unbiodegradable COD (40 ± 3), (0.06), particulate unbiodegradable COD (53 ± 3) (0.08), total TKN (40 ± 4) mg/L, ammonia (28 ± 6), (0.68), organically bound nitrogen (12 ± 2), (0.32), TP (15 ± 1.4), orthophosphates (9.6 ± 1.4), (0.64), and organically bound TP (5.4 ± 1.4), (0.36), soluble unbiodegradable TP (0.4 ± 0), (0.03), particulate unbiodegradable TP (0.05 ± 0), (0.003). Thus, wastewater at Firle STW was found to be highly biodegradable suggesting optimisation of biological nutrient removal process will generally achieve effluent regulatory standards compliance. Thus, opportunities for plant optimisation do exist of which modelling with the use of a simulator is recommended to achieve recommended effluent standards in addition to reduction of operating costs.

Optimisation of reconstruction--reprojection-based motion correction for cardiac SPECT.

PubMed

Kangasmaa, Tuija S; Sohlberg, Antti O

2014-07-01

Cardiac motion is a challenging cause of image artefacts in myocardial perfusion SPECT. A wide range of motion correction methods have been developed over the years, and so far automatic algorithms based on the reconstruction--reprojection principle have proved to be the most effective. However, these methods have not been fully optimised in terms of their free parameters and implementational details. Two slightly different implementations of reconstruction--reprojection-based motion correction techniques were optimised for effective, good-quality motion correction and then compared with each other. The first of these methods (Method 1) was the traditional reconstruction-reprojection motion correction algorithm, where the motion correction is done in projection space, whereas the second algorithm (Method 2) performed motion correction in reconstruction space. The parameters that were optimised include the type of cost function (squared difference, normalised cross-correlation and mutual information) that was used to compare measured and reprojected projections, and the number of iterations needed. The methods were tested with motion-corrupt projection datasets, which were generated by adding three different types of motion (lateral shift, vertical shift and vertical creep) to motion-free cardiac perfusion SPECT studies. Method 2 performed slightly better overall than Method 1, but the difference between the two implementations was small. The execution time for Method 2 was much longer than for Method 1, which limits its clinical usefulness. The mutual information cost function gave clearly the best results for all three motion sets for both correction methods. Three iterations were sufficient for a good quality correction using Method 1. The traditional reconstruction--reprojection-based method with three update iterations and mutual information cost function is a good option for motion correction in clinical myocardial perfusion SPECT.

CMOS analogue amplifier circuits optimisation using hybrid backtracking search algorithm with differential evolution

NASA Astrophysics Data System (ADS)

Mallick, S.; Kar, R.; Mandal, D.; Ghoshal, S. P.

2016-07-01

This paper proposes a novel hybrid optimisation algorithm which combines the recently proposed evolutionary algorithm Backtracking Search Algorithm (BSA) with another widely accepted evolutionary algorithm, namely, Differential Evolution (DE). The proposed algorithm called BSA-DE is employed for the optimal designs of two commonly used analogue circuits, namely Complementary Metal Oxide Semiconductor (CMOS) differential amplifier circuit with current mirror load and CMOS two-stage operational amplifier (op-amp) circuit. BSA has a simple structure that is effective, fast and capable of solving multimodal problems. DE is a stochastic, population-based heuristic approach, having the capability to solve global optimisation problems. In this paper, the transistors' sizes are optimised using the proposed BSA-DE to minimise the areas occupied by the circuits and to improve the performances of the circuits. The simulation results justify the superiority of BSA-DE in global convergence properties and fine tuning ability, and prove it to be a promising candidate for the optimal design of the analogue CMOS amplifier circuits. The simulation results obtained for both the amplifier circuits prove the effectiveness of the proposed BSA-DE-based approach over DE, harmony search (HS), artificial bee colony (ABC) and PSO in terms of convergence speed, design specifications and design parameters of the optimal design of the analogue CMOS amplifier circuits. It is shown that BSA-DE-based design technique for each amplifier circuit yields the least MOS transistor area, and each designed circuit is shown to have the best performance parameters such as gain, power dissipation, etc., as compared with those of other recently reported literature.

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

NASA Astrophysics Data System (ADS)

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.

Study on the extrusion of nickel-based spark plug electrodes by numerical simulation

NASA Astrophysics Data System (ADS)

Saby, Q.; Courbon, C.; Salvatore, F.; Fabre, D.; Romeyer, F.

2018-05-01

Interest in metal forming simulation has grown rapidly during the last decades and is now well established even in industry. It provides a flexible and relatively cheap method to perform sensitivity analyses, getting a better insight into the forming process and use it as an optimisation tool. As far as wear is concerned, numerical simulation can be seen as a relevant approach to assess the thermomechanical loadings applied to the active die surface and therefore predict their wear behaviour. In this study, a Finite-Element (FE) based model has been developed in order to investigate the cold forming process of a nickel-based sparkplug electrode. A fully thermo-mechanically coupled implicit formulation has been used in order to model the forward extrusion step with a special emphasis on the contact conditions at the workpiece-die interface. Contact pressure, relative sliding velocity and temperature profiles have been extracted versus time and qualitatively compared to the wear phenomena observed on the worn production dies.

Optimal control of LQR for discrete time-varying systems with input delays

NASA Astrophysics Data System (ADS)

Yin, Yue-Zhu; Yang, Zhong-Lian; Yin, Zhi-Xiang; Xu, Feng

2018-04-01

In this work, we consider the optimal control problem of linear quadratic regulation for discrete time-variant systems with single input and multiple input delays. An innovative and simple method to derive the optimal controller is given. The studied problem is first equivalently converted into a problem subject to a constraint condition. Last, with the established duality, the problem is transformed into a static mathematical optimisation problem without input delays. The optimal control input solution to minimise performance index function is derived by solving this optimisation problem with two methods. A numerical simulation example is carried out and its results show that our two approaches are both feasible and very effective.

Topology optimisation of micro fluidic mixers considering fluid-structure interactions with a coupled Lattice Boltzmann algorithm

NASA Astrophysics Data System (ADS)

Munk, David J.; Kipouros, Timoleon; Vio, Gareth A.; Steven, Grant P.; Parks, Geoffrey T.

2017-11-01

Recently, the study of micro fluidic devices has gained much interest in various fields from biology to engineering. In the constant development cycle, the need to optimise the topology of the interior of these devices, where there are two or more optimality criteria, is always present. In this work, twin physical situations, whereby optimal fluid mixing in the form of vorticity maximisation is accompanied by the requirement that the casing in which the mixing takes place has the best structural performance in terms of the greatest specific stiffness, are considered. In the steady state of mixing this also means that the stresses in the casing are as uniform as possible, thus giving a desired operating life with minimum weight. The ultimate aim of this research is to couple two key disciplines, fluids and structures, into a topology optimisation framework, which shows fast convergence for multidisciplinary optimisation problems. This is achieved by developing a bi-directional evolutionary structural optimisation algorithm that is directly coupled to the Lattice Boltzmann method, used for simulating the flow in the micro fluidic device, for the objectives of minimum compliance and maximum vorticity. The needs for the exploration of larger design spaces and to produce innovative designs make meta-heuristic algorithms, such as genetic algorithms, particle swarms and Tabu Searches, less efficient for this task. The multidisciplinary topology optimisation framework presented in this article is shown to increase the stiffness of the structure from the datum case and produce physically acceptable designs. Furthermore, the topology optimisation method outperforms a Tabu Search algorithm in designing the baffle to maximise the mixing of the two fluids.

Collaborative development for setup, execution, sharing and analytics of complex NMR experiments.

PubMed

Irvine, Alistair G; Slynko, Vadim; Nikolaev, Yaroslav; Senthamarai, Russell R P; Pervushin, Konstantin

2014-02-01

Factory settings of NMR pulse sequences are rarely ideal for every scenario in which they are utilised. The optimisation of NMR experiments has for many years been performed locally, with implementations often specific to an individual spectrometer. Furthermore, these optimised experiments are normally retained solely for the use of an individual laboratory, spectrometer or even single user. Here we introduce a web-based service that provides a database for the deposition, annotation and optimisation of NMR experiments. The application uses a Wiki environment to enable the collaborative development of pulse sequences. It also provides a flexible mechanism to automatically generate NMR experiments from deposited sequences. Multidimensional NMR experiments of proteins and other macromolecules consume significant resources, in terms of both spectrometer time and effort required to analyse the results. Systematic analysis of simulated experiments can enable optimal allocation of NMR resources for structural analysis of proteins. Our web-based application (http://nmrplus.org) provides all the necessary information, includes the auxiliaries (waveforms, decoupling sequences etc.), for analysis of experiments by accurate numerical simulation of multidimensional NMR experiments. The online database of the NMR experiments, together with a systematic evaluation of their sensitivity, provides a framework for selection of the most efficient pulse sequences. The development of such a framework provides a basis for the collaborative optimisation of pulse sequences by the NMR community, with the benefits of this collective effort being available to the whole community. Copyright © 2013 Elsevier Inc. All rights reserved.

Optimisation of warpage on thin shell part by using particle swarm optimisation (PSO)

NASA Astrophysics Data System (ADS)

Norshahira, R.; Shayfull, Z.; Nasir, S. M.; Saad, S. M. Sazli; Fathullah, M.

2017-09-01

As the product nowadays moving towards thinner design, causing the production of the plastic product facing a lot of difficulties. This is due to the higher possibilities of defects occur as the thickness of the wall gets thinner. Demand for technique in reducing the defects increasing due to this factor. These defects has seen to be occur due to several factors in injection moulding process. In the study a Moldflow software was used in simulating the injection moulding process. While RSM is used in producing the mathematical model to be used as the input fitness function for the Matlab software. Particle Swarm Optimisation (PSO) technique is used in optimising the processing condition to reduce the amount of shrinkage and warpage of the plastic part. The results shows that there are a warpage reduction of 17.60% in x direction, 18.15% in y direction and 10.25% reduction in z direction respectively. The results shows the reliability of this artificial method in minimising the product warpage.

Set-membership fault detection under noisy environment with application to the detection of abnormal aircraft control surface positions

NASA Astrophysics Data System (ADS)

El Houda Thabet, Rihab; Combastel, Christophe; Raïssi, Tarek; Zolghadri, Ali

2015-09-01

The paper develops a set membership detection methodology which is applied to the detection of abnormal positions of aircraft control surfaces. Robust and early detection of such abnormal positions is an important issue for early system reconfiguration and overall optimisation of aircraft design. In order to improve fault sensitivity while ensuring a high level of robustness, the method combines a data-driven characterisation of noise and a model-driven approach based on interval prediction. The efficiency of the proposed methodology is illustrated through simulation results obtained based on data recorded in several flight scenarios of a highly representative aircraft benchmark.

Comparing approaches for using climate projections in assessing water resources investments for systems with multiple stakeholder groups

NASA Astrophysics Data System (ADS)

Hurford, Anthony; Harou, Julien

2015-04-01

Climate change has challenged conventional methods of planning water resources infrastructure investment, relying on stationarity of time-series data. It is not clear how to best use projections of future climatic conditions. Many-objective simulation-optimisation and trade-off analysis using evolutionary algorithms has been proposed as an approach to addressing complex planning problems with multiple conflicting objectives. The search for promising assets and policies can be carried out across a range of climate projections, to identify the configurations of infrastructure investment shown by model simulation to be robust under diverse future conditions. Climate projections can be used in different ways within a simulation model to represent the range of possible future conditions and understand how optimal investments vary according to the different hydrological conditions. We compare two approaches, optimising over an ensemble of different 20-year flow and PET timeseries projections, and separately for individual future scenarios built synthetically from the original ensemble. Comparing trade-off curves and surfaces generated by the two approaches helps understand the limits and benefits of optimising under different sets of conditions. The comparison is made for the Tana Basin in Kenya, where climate change combined with multiple conflicting objectives of water management and infrastructure investment mean decision-making is particularly challenging.

The development of response surface pathway design to reduce animal numbers in toxicity studies

PubMed Central

2014-01-01

Background This study describes the development of Response Surface Pathway (RSP) design, assesses its performance and effectiveness in estimating LD50, and compares RSP with Up and Down Procedures (UDPs) and Random Walk (RW) design. Methods A basic 4-level RSP design was used on 36 male ICR mice given intraperitoneal doses of Yessotoxin. Simulations were performed to optimise the design. A k-adjustment factor was introduced to ensure coverage of the dose window and calculate the dose steps. Instead of using equal numbers of mice on all levels, the number of mice was increased at each design level. Additionally, the binomial outcome variable was changed to multinomial. The performance of the RSP designs and a comparison of UDPs and RW were assessed by simulations. The optimised 4-level RSP design was used on 24 female NMRI mice given Azaspiracid-1 intraperitoneally. Results The in vivo experiment with basic 4-level RSP design estimated the LD50 of Yessotoxin to be 463 μg/kgBW (95% CI: 383–535). By inclusion of the k-adjustment factor with equal or increasing numbers of mice on increasing dose levels, the estimate changed to 481 μg/kgBW (95% CI: 362–566) and 447 μg/kgBW (95% CI: 378–504 μg/kgBW), respectively. The optimised 4-level RSP estimated the LD50 to be 473 μg/kgBW (95% CI: 442–517). A similar increase in power was demonstrated using the optimised RSP design on real Azaspiracid-1 data. The simulations showed that the inclusion of the k-adjustment factor, reduction in sample size by increasing the number of mice on higher design levels and incorporation of a multinomial outcome gave estimates of the LD50 that were as good as those with the basic RSP design. Furthermore, optimised RSP design performed on just three levels reduced the number of animals from 36 to 15 without loss of information, when compared with the 4-level designs. Simulated comparison of the RSP design with UDPs and RW design demonstrated the superiority of RSP. Conclusion Optimised RSP design reduces the number of animals needed. The design converges rapidly on the area of interest and is at least as efficient as both the UDPs and RW design. PMID:24661560

A Galerkin discretisation-based identification for parameters in nonlinear mechanical systems

NASA Astrophysics Data System (ADS)

Liu, Zuolin; Xu, Jian

2018-04-01

In the paper, a new parameter identification method is proposed for mechanical systems. Based on the idea of Galerkin finite-element method, the displacement over time history is approximated by piecewise linear functions, and the second-order terms in model equation are eliminated by integrating by parts. In this way, the lost function of integration form is derived. Being different with the existing methods, the lost function actually is a quadratic sum of integration over the whole time history. Then for linear or nonlinear systems, the optimisation of the lost function can be applied with traditional least-squares algorithm or the iterative one, respectively. Such method could be used to effectively identify parameters in linear and arbitrary nonlinear mechanical systems. Simulation results show that even under the condition of sparse data or low sampling frequency, this method could still guarantee high accuracy in identifying linear and nonlinear parameters.

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

PubMed

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 novel specimen-specific methodology to optimise the alignment of long bones for experimental testing.

PubMed

Cheong, Vee San; Bull, Anthony M J

2015-12-16

The choice of coordinate system and alignment of bone will affect the quantification of mechanical properties obtained during in-vitro biomechanical testing. Where these are used in predictive models, such as finite element analysis, the fidelic description of these properties is paramount. Currently in bending and torsional tests, bones are aligned on a pre-defined fixed span based on the reference system marked out. However, large inter-specimen differences have been reported. This suggests a need for the development of a specimen-specific alignment system for use in experimental work. Eleven ovine tibiae were used in this study and three-dimensional surface meshes were constructed from micro-Computed Tomography scan images. A novel, semi-automated algorithm was developed and applied to the surface meshes to align the whole bone based on its calculated principal directions. Thereafter, the code isolates the optimised location and length of each bone for experimental testing. This resulted in a lowering of the second moment of area about the chosen bending axis in the central region. More importantly, the optimisation method decreases the irregularity of the shape of the cross-sectional slices as the unbiased estimate of the population coefficient of variation of the second moment of area decreased from a range of (0.210-0.435) to (0.145-0.317) in the longitudinal direction, indicating a minimisation of the product moment, which causes eccentric loading. Thus, this methodology serves as an important pre-step to align the bone for mechanical tests or simulation work, is optimised for each specimen, ensures repeatability, and is general enough to be applied to any long bone. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model

NASA Astrophysics Data System (ADS)

Wadoux, Alexandre M. J.-C.; Brus, Dick J.; Rico-Ramirez, Miguel A.; Heuvelink, Gerard B. M.

2017-09-01

The accuracy of spatial predictions of rainfall by merging rain-gauge and radar data is partly determined by the sampling design of the rain-gauge network. Optimising the locations of the rain-gauges may increase the accuracy of the predictions. Existing spatial sampling design optimisation methods are based on minimisation of the spatially averaged prediction error variance under the assumption of intrinsic stationarity. Over the past years, substantial progress has been made to deal with non-stationary spatial processes in kriging. Various well-documented geostatistical models relax the assumption of stationarity in the mean, while recent studies show the importance of considering non-stationarity in the variance for environmental processes occurring in complex landscapes. We optimised the sampling locations of rain-gauges using an extension of the Kriging with External Drift (KED) model for prediction of rainfall fields. The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage. Spatial predictions are made repeatedly over time, each time recalibrating the model. The space-time averaged KED variance was minimised by Spatial Simulated Annealing (SSA). The methodology was tested using a case study predicting daily rainfall in the north of England for a one-year period. Results show that (i) the proposed non-stationary variance model outperforms the stationary variance model, and (ii) a small but significant decrease of the rainfall prediction error variance is obtained with the optimised rain-gauge network. In particular, it pays off to place rain-gauges at locations where the radar imagery is inaccurate, while keeping the distribution over the study area sufficiently uniform.

On the use of PGD for optimal control applied to automated fibre placement

NASA Astrophysics Data System (ADS)

Bur, N.; Joyot, P.

2017-10-01

Automated Fibre Placement (AFP) is an incipient manufacturing process for composite structures. Despite its concep-tual simplicity it involves many complexities related to the necessity of melting the thermoplastic at the interface tape-substrate, ensuring the consolidation that needs the diffusion of molecules and control the residual stresses installation responsible of the residual deformations of the formed parts. The optimisation of the process and the determination of the process window cannot be achieved in a traditional way since it requires a plethora of trials/errors or numerical simulations, because there are many parameters involved in the characterisation of the material and the process. Using reduced order modelling such as the so called Proper Generalised Decomposition method, allows the construction of multi-parametric solution taking into account many parameters. This leads to virtual charts that can be explored on-line in real time in order to perform process optimisation or on-line simulation-based control. Thus, for a given set of parameters, determining the power leading to an optimal temperature becomes easy. However, instead of controlling the power knowing the temperature field by particularizing an abacus, we propose here an approach based on optimal control: we solve by PGD a dual problem from heat equation and optimality criteria. To circumvent numerical issue due to ill-conditioned system, we propose an algorithm based on Uzawa's method. That way, we are able to solve the dual problem, setting the desired state as an extra-coordinate in the PGD framework. In a single computation, we get both the temperature field and the required heat flux to reach a parametric optimal temperature on a given zone.

Mixing formula for tissue-mimicking silicone phantoms in the near infrared

NASA Astrophysics Data System (ADS)

Böcklin, C.; Baumann, D.; Stuker, F.; Fröhlich, Jürg

2015-03-01

The knowledge of accurate optical parameters of materials is paramount in biomedical optics applications and numerical simulations of such systems. Phantom materials with variable but predefined parameters are needed to optimise these systems. An optimised integrating sphere measurement setup and reconstruction algorithm are presented in this work to determine the optical properties of silicone rubber based phantoms whose absorption and scattering properties are altered with TiO2 and carbon black particles. A mixing formula for all constituents is derived and allows to create phantoms with predefined optical properties.

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

NASA Astrophysics Data System (ADS)

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.

Simulations of multi-contrast x-ray imaging using near-field speckles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zdora, Marie-Christine; Diamond Light Source, Harwell Science and Innovation Campus, Didcot, Oxfordshire, OX11 0DE, United Kingdom and Department of Physics & Astronomy, University College London, London, WC1E 6BT; Thibault, Pierre

2016-01-28

X-ray dark-field and phase-contrast imaging using near-field speckles is a novel technique that overcomes limitations inherent in conventional absorption x-ray imaging, i.e. poor contrast for features with similar density. Speckle-based imaging yields a wealth of information with a simple setup tolerant to polychromatic and divergent beams, and simple data acquisition and analysis procedures. Here, we present a simulation software used to model the image formation with the speckle-based technique, and we compare simulated results on a phantom sample with experimental synchrotron data. Thorough simulation of a speckle-based imaging experiment will help for better understanding and optimising the technique itself.

A target recognition method for maritime surveillance radars based on hybrid ensemble selection

NASA Astrophysics Data System (ADS)

Fan, Xueman; Hu, Shengliang; He, Jingbo

2017-11-01

In order to improve the generalisation ability of the maritime surveillance radar, a novel ensemble selection technique, termed Optimisation and Dynamic Selection (ODS), is proposed. During the optimisation phase, the non-dominated sorting genetic algorithm II for multi-objective optimisation is used to find the Pareto front, i.e. a set of ensembles of classifiers representing different tradeoffs between the classification error and diversity. During the dynamic selection phase, the meta-learning method is used to predict whether a candidate ensemble is competent enough to classify a query instance based on three different aspects, namely, feature space, decision space and the extent of consensus. The classification performance and time complexity of ODS are compared against nine other ensemble methods using a self-built full polarimetric high resolution range profile data-set. The experimental results clearly show the effectiveness of ODS. In addition, the influence of the selection of diversity measures is studied concurrently.

Boundary element based multiresolution shape optimisation in electrostatics

NASA Astrophysics Data System (ADS)

Bandara, Kosala; Cirak, Fehmi; Of, Günther; Steinbach, Olaf; Zapletal, Jan

2015-09-01

We consider the shape optimisation of high-voltage devices subject to electrostatic field equations by combining fast boundary elements with multiresolution subdivision surfaces. The geometry of the domain is described with subdivision surfaces and different resolutions of the same geometry are used for optimisation and analysis. The primal and adjoint problems are discretised with the boundary element method using a sufficiently fine control mesh. For shape optimisation the geometry is updated starting from the coarsest control mesh with increasingly finer control meshes. The multiresolution approach effectively prevents the appearance of non-physical geometry oscillations in the optimised shapes. Moreover, there is no need for mesh regeneration or smoothing during the optimisation due to the absence of a volume mesh. We present several numerical experiments and one industrial application to demonstrate the robustness and versatility of the developed approach.

Optimising the Parallelisation of OpenFOAM Simulations

DTIC Science & Technology

2014-06-01

UNCLASSIFIED UNCLASSIFIED Optimising the Parallelisation of OpenFOAM Simulations Shannon Keough Maritime Division Defence...Science and Technology Organisation DSTO-TR-2987 ABSTRACT The OpenFOAM computational fluid dynamics toolbox allows parallel computation of...performance of a given high performance computing cluster with several OpenFOAM cases, running using a combination of MPI libraries and corresponding MPI

Man vs. Machine: An interactive poll to evaluate hydrological model performance of a manual and an automatic calibration

NASA Astrophysics Data System (ADS)

Wesemann, Johannes; Burgholzer, Reinhard; Herrnegger, Mathew; Schulz, Karsten

2017-04-01

In recent years, a lot of research in hydrological modelling has been invested to improve the automatic calibration of rainfall-runoff models. This includes for example (1) the implementation of new optimisation methods, (2) the incorporation of new and different objective criteria and signatures in the optimisation and (3) the usage of auxiliary data sets apart from runoff. Nevertheless, in many applications manual calibration is still justifiable and frequently applied. The hydrologist performing the manual calibration, with his expert knowledge, is able to judge the hydrographs simultaneously concerning details but also in a holistic view. This integrated eye-ball verification procedure available to man can be difficult to formulate in objective criteria, even when using a multi-criteria approach. Comparing the results of automatic and manual calibration is not straightforward. Automatic calibration often solely involves objective criteria such as Nash-Sutcliffe Efficiency Coefficient or the Kling-Gupta-Efficiency as a benchmark during the calibration. Consequently, a comparison based on such measures is intrinsically biased towards automatic calibration. Additionally, objective criteria do not cover all aspects of a hydrograph leaving questions concerning the quality of a simulation open. This contribution therefore seeks to examine the quality of manually and automatically calibrated hydrographs by interactively involving expert knowledge in the evaluation. Simulations have been performed for the Mur catchment in Austria with the rainfall-runoff model COSERO using two parameter sets evolved from a manual and an automatic calibration. A subset of resulting hydrographs for observation and simulation, representing the typical flow conditions and events, will be evaluated in this study. In an interactive crowdsourcing approach experts attending the session can vote for their preferred simulated hydrograph without having information on the calibration method that produced the respective hydrograph. Therefore, the result of the poll can be seen as an additional quality criterion for the comparison of the two different approaches and help in the evaluation of the automatic calibration method.

An improved PSO-SVM model for online recognition defects in eddy current testing

NASA Astrophysics Data System (ADS)

Liu, Baoling; Hou, Dibo; Huang, Pingjie; Liu, Banteng; Tang, Huayi; Zhang, Wubo; Chen, Peihua; Zhang, Guangxin

2013-12-01

Accurate and rapid recognition of defects is essential for structural integrity and health monitoring of in-service device using eddy current (EC) non-destructive testing. This paper introduces a novel model-free method that includes three main modules: a signal pre-processing module, a classifier module and an optimisation module. In the signal pre-processing module, a kind of two-stage differential structure is proposed to suppress the lift-off fluctuation that could contaminate the EC signal. In the classifier module, multi-class support vector machine (SVM) based on one-against-one strategy is utilised for its good accuracy. In the optimisation module, the optimal parameters of classifier are obtained by an improved particle swarm optimisation (IPSO) algorithm. The proposed IPSO technique can improve convergence performance of the primary PSO through the following strategies: nonlinear processing of inertia weight, introductions of the black hole and simulated annealing model with extremum disturbance. The good generalisation ability of the IPSO-SVM model has been validated through adding additional specimen into the testing set. Experiments show that the proposed algorithm can achieve higher recognition accuracy and efficiency than other well-known classifiers and the superiorities are more obvious with less training set, which contributes to online application.

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.

PubMed

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.

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

PubMed Central

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. PMID:24151522

Circuit-based versus full-wave modelling of active microwave circuits

NASA Astrophysics Data System (ADS)

Bukvić, Branko; Ilić, Andjelija Ž.; Ilić, Milan M.

2018-03-01

Modern full-wave computational tools enable rigorous simulations of linear parts of complex microwave circuits within minutes, taking into account all physical electromagnetic (EM) phenomena. Non-linear components and other discrete elements of the hybrid microwave circuit are then easily added within the circuit simulator. This combined full-wave and circuit-based analysis is a must in the final stages of the circuit design, although initial designs and optimisations are still faster and more comfortably done completely in the circuit-based environment, which offers real-time solutions at the expense of accuracy. However, due to insufficient information and general lack of specific case studies, practitioners still struggle when choosing an appropriate analysis method, or a component model, because different choices lead to different solutions, often with uncertain accuracy and unexplained discrepancies arising between the simulations and measurements. We here design a reconfigurable power amplifier, as a case study, using both circuit-based solver and a full-wave EM solver. We compare numerical simulations with measurements on the manufactured prototypes, discussing the obtained differences, pointing out the importance of measured parameters de-embedding, appropriate modelling of discrete components and giving specific recipes for good modelling practices.

A joint swarm intelligence algorithm for multi-user detection in MIMO-OFDM system

NASA Astrophysics Data System (ADS)

Hu, Fengye; Du, Dakun; Zhang, Peng; Wang, Zhijun

2014-11-01

In the multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system, traditional multi-user detection (MUD) algorithms that usually used to suppress multiple access interference are difficult to balance system detection performance and the complexity of the algorithm. To solve this problem, this paper proposes a joint swarm intelligence algorithm called Ant Colony and Particle Swarm Optimisation (AC-PSO) by integrating particle swarm optimisation (PSO) and ant colony optimisation (ACO) algorithms. According to simulation results, it has been shown that, with low computational complexity, the MUD for the MIMO-OFDM system based on AC-PSO algorithm gains comparable MUD performance with maximum likelihood algorithm. Thus, the proposed AC-PSO algorithm provides a satisfactory trade-off between computational complexity and detection performance.

Single tube genotyping of sickle cell anaemia using PCR-based SNP analysis.

PubMed

Waterfall, C M; Cobb, B D

2001-12-01

Allele-specific amplification (ASA) is a generally applicable technique for the detection of known single nucleotide polymorphisms (SNPs), deletions, insertions and other sequence variations. Conventionally, two reactions are required to determine the zygosity of DNA in a two-allele system, along with significant upstream optimisation to define the specific test conditions. Here, we combine single tube bi-directional ASA with a 'matrix-based' optimisation strategy, speeding up the whole process in a reduced reaction set. We use sickle cell anaemia as our model SNP system, a genetic disease that is currently screened using ASA methods. Discriminatory conditions were rapidly optimised enabling the unambiguous identification of DNA from homozygous sickle cell patients (HbS/S), heterozygous carriers (HbA/S) or normal DNA in a single tube. Simple downstream mathematical analyses based on product yield across the optimisation set allow an insight into the important aspects of priming competition and component interactions in this competitive PCR. This strategy can be applied to any polymorphism, defining specific conditions using a multifactorial approach. The inherent simplicity and low cost of this PCR-based method validates bi-directional ASA as an effective tool in future clinical screening and pharmacogenomic research where more expensive fluorescence-based approaches may not be desirable.

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

NASA Astrophysics Data System (ADS)

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.

Vertical transportation systems embedded on shuffled frog leaping algorithm for manufacturing optimisation problems in industries.

PubMed

Aungkulanon, Pasura; Luangpaiboon, Pongchanun

2016-01-01

Response surface methods via the first or second order models are important in manufacturing processes. This study, however, proposes different structured mechanisms of the vertical transportation systems or VTS embedded on a shuffled frog leaping-based approach. There are three VTS scenarios, a motion reaching a normal operating velocity, and both reaching and not reaching transitional motion. These variants were performed to simultaneously inspect multiple responses affected by machining parameters in multi-pass turning processes. The numerical results of two machining optimisation problems demonstrated the high performance measures of the proposed methods, when compared to other optimisation algorithms for an actual deep cut design.

Optimisation potential for a SBR plant based upon integrated modelling for dry and wet weather conditions.

PubMed

Rönner-Holm, S G E; Kaufmann Alves, I; Steinmetz, H; Holm, N C

2009-01-01

Integrated dynamic simulation analysis of a full-scale municipal sequential batch reactor (SBR) wastewater treatment plant (WWTP) was performed using the KOSMO pollution load simulation model for the combined sewer system (CSS) and the ASM3 + EAWAG-BioP model for the WWTP. Various optimising strategies for dry and storm weather conditions were developed to raise the purification and hydraulic performance and to reduce operation costs based on simulation studies with the calibrated WWTP model. The implementation of some strategies on the plant led to lower effluent values and an average annual saving of 49,000 euro including sewage tax, which is 22% of the total running costs. Dynamic simulation analysis of CSS for an increased WWTP influent over a period of one year showed high potentials for reducing combined sewer overflow (CSO) volume by 18-27% and CSO loads for COD by 22%, NH(4)-N and P(total) by 33%. In addition, the SBR WWTP could easily handle much higher influents without exceeding the monitoring values. During the integrated simulation of representative storm events, the total emission load for COD dropped to 90%, the sewer system emitted 47% less, whereas the pollution load in the WWTP effluent increased to only 14% with 2% higher running costs.

Metaheuristic optimisation methods for approximate solving of singular boundary value problems

NASA Astrophysics Data System (ADS)

Sadollah, Ali; Yadav, Neha; Gao, Kaizhou; Su, Rong

2017-07-01

This paper presents a novel approximation technique based on metaheuristics and weighted residual function (WRF) for tackling singular boundary value problems (BVPs) arising in engineering and science. With the aid of certain fundamental concepts of mathematics, Fourier series expansion, and metaheuristic optimisation algorithms, singular BVPs can be approximated as an optimisation problem with boundary conditions as constraints. The target is to minimise the WRF (i.e. error function) constructed in approximation of BVPs. The scheme involves generational distance metric for quality evaluation of the approximate solutions against exact solutions (i.e. error evaluator metric). Four test problems including two linear and two non-linear singular BVPs are considered in this paper to check the efficiency and accuracy of the proposed algorithm. The optimisation task is performed using three different optimisers including the particle swarm optimisation, the water cycle algorithm, and the harmony search algorithm. Optimisation results obtained show that the suggested technique can be successfully applied for approximate solving of singular BVPs.

A new web-based modelling tool (Websim-MILQ) aimed at optimisation of thermal treatments in the dairy industry.

PubMed

Schutyser, M A I; Straatsma, J; Keijzer, P M; Verschueren, M; De Jong, P

2008-11-30

In the framework of a cooperative EU research project (MILQ-QC-TOOL) a web-based modelling tool (Websim-MILQ) was developed for optimisation of thermal treatments in the dairy industry. The web-based tool enables optimisation of thermal treatments with respect to product safety, quality and costs. It can be applied to existing products and processes but also to reduce time to market for new products. Important aspects of the tool are its user-friendliness and its specifications customised to the needs of small dairy companies. To challenge the web-based tool it was applied for optimisation of thermal treatments in 16 dairy companies producing yoghurt, fresh cream, chocolate milk and cheese. Optimisation with WebSim-MILQ resulted in concrete improvements with respect to risk of microbial contamination, cheese yield, fouling and production costs. In this paper we illustrate the use of WebSim-MILQ for optimisation of a cheese milk pasteurisation process where we could increase the cheese yield (1 extra cheese for each 100 produced cheeses from the same amount of milk) and reduced the risk of contamination of pasteurised cheese milk with thermoresistent streptococci from critical to negligible. In another case we demonstrate the advantage for changing from an indirect to a direct heating method for a UHT process resulting in 80% less fouling, while improving product quality and maintaining product safety.

Single tube genotyping of sickle cell anaemia using PCR-based SNP analysis

PubMed Central

Waterfall, Christy M.; Cobb, Benjamin D.

2001-01-01

Allele-specific amplification (ASA) is a generally applicable technique for the detection of known single nucleotide polymorphisms (SNPs), deletions, insertions and other sequence variations. Conventionally, two reactions are required to determine the zygosity of DNA in a two-allele system, along with significant upstream optimisation to define the specific test conditions. Here, we combine single tube bi-directional ASA with a ‘matrix-based’ optimisation strategy, speeding up the whole process in a reduced reaction set. We use sickle cell anaemia as our model SNP system, a genetic disease that is currently screened using ASA methods. Discriminatory conditions were rapidly optimised enabling the unambiguous identification of DNA from homozygous sickle cell patients (HbS/S), heterozygous carriers (HbA/S) or normal DNA in a single tube. Simple downstream mathematical analyses based on product yield across the optimisation set allow an insight into the important aspects of priming competition and component interactions in this competitive PCR. This strategy can be applied to any polymorphism, defining specific conditions using a multifactorial approach. The inherent simplicity and low cost of this PCR-based method validates bi-directional ASA as an effective tool in future clinical screening and pharmacogenomic research where more expensive fluorescence-based approaches may not be desirable. PMID:11726702

Development and validation of real-time simulation of X-ray imaging with respiratory motion.

PubMed

Vidal, Franck P; Villard, Pierre-Frédéric

2016-04-01

We present a framework that combines evolutionary optimisation, soft tissue modelling and ray tracing on GPU to simultaneously compute the respiratory motion and X-ray imaging in real-time. Our aim is to provide validated building blocks with high fidelity to closely match both the human physiology and the physics of X-rays. A CPU-based set of algorithms is presented to model organ behaviours during respiration. Soft tissue deformation is computed with an extension of the Chain Mail method. Rigid elements move according to kinematic laws. A GPU-based surface rendering method is proposed to compute the X-ray image using the Beer-Lambert law. It is provided as an open-source library. A quantitative validation study is provided to objectively assess the accuracy of both components: (i) the respiration against anatomical data, and (ii) the X-ray against the Beer-Lambert law and the results of Monte Carlo simulations. Our implementation can be used in various applications, such as interactive medical virtual environment to train percutaneous transhepatic cholangiography in interventional radiology, 2D/3D registration, computation of digitally reconstructed radiograph, simulation of 4D sinograms to test tomography reconstruction tools. Copyright © 2015 Elsevier Ltd. All rights reserved.

Experimental design-based isotope-dilution SPME-GC/MS method development for the analysis of smoke flavouring products.

PubMed

Giri, Anupam; Zelinkova, Zuzana; Wenzl, Thomas

2017-12-01

For the implementation of Regulation (EC) No 2065/2003 related to smoke flavourings used or intended for use in or on foods a method based on solid-phase micro extraction (SPME) GC/MS was developed for the characterisation of liquid smoke products. A statistically based experimental design (DoE) was used for method optimisation. The best general conditions to quantitatively analyse the liquid smoke compounds were obtained with a polydimethylsiloxane/divinylbenzene (PDMS/DVB) fibre, 60°C extraction temperature, 30 min extraction time, 250°C desorption temperature, 180 s desorption time, 15 s agitation time, and 250 rpm agitation speed. Under the optimised conditions, 119 wood pyrolysis products including furan/pyran derivatives, phenols, guaiacol, syringol, benzenediol, and their derivatives, cyclic ketones, and several other heterocyclic compounds were identified. The proposed method was repeatable (RSD% <5) and the calibration functions were linear for all compounds under study. Nine isotopically labelled internal standards were used for improving quantification of analytes by compensating matrix effects that might affect headspace equilibrium and extractability of compounds. The optimised isotope dilution SPME-GC/MS based analytical method proved to be fit for purpose, allowing the rapid identification and quantification of volatile compounds in liquid smoke flavourings.

Model structure identification for wastewater treatment simulation based on computational fluid dynamics.

PubMed

Alex, J; Kolisch, G; Krause, K

2002-01-01

The objective of this presented project is to use the results of an CFD simulation to automatically, systematically and reliably generate an appropriate model structure for simulation of the biological processes using CSTR activated sludge compartments. Models and dynamic simulation have become important tools for research but also increasingly for the design and optimisation of wastewater treatment plants. Besides the biological models several cases are reported about the application of computational fluid dynamics ICFD) to wastewater treatment plants. One aim of the presented method to derive model structures from CFD results is to exclude the influence of empirical structure selection to the result of dynamic simulations studies of WWTPs. The second application of the approach developed is the analysis of badly performing treatment plants where the suspicion arises that bad flow behaviour such as short cut flows is part of the problem. The method suggested requires as the first step the calculation of fluid dynamics of the biological treatment step at different loading situations by use of 3-dimensional CFD simulation. The result of this information is used to generate a suitable model structure for conventional dynamic simulation of the treatment plant by use of a number of CSTR modules with a pattern of exchange flows between the tanks automatically. The method is explained in detail and the application to the WWTP Wuppertal Buchenhofen is presented.

pyPcazip: A PCA-based toolkit for compression and analysis of molecular simulation data

NASA Astrophysics Data System (ADS)

Shkurti, Ardita; Goni, Ramon; Andrio, Pau; Breitmoser, Elena; Bethune, Iain; Orozco, Modesto; Laughton, Charles A.

The biomolecular simulation community is currently in need of novel and optimised software tools that can analyse and process, in reasonable timescales, the large generated amounts of molecular simulation data. In light of this, we have developed and present here pyPcazip: a suite of software tools for compression and analysis of molecular dynamics (MD) simulation data. The software is compatible with trajectory file formats generated by most contemporary MD engines such as AMBER, CHARMM, GROMACS and NAMD, and is MPI parallelised to permit the efficient processing of very large datasets. pyPcazip is a Unix based open-source software (BSD licenced) written in Python.

Calibrating reaction rates for the CREST model

NASA Astrophysics Data System (ADS)

Handley, Caroline A.; Christie, Michael A.

2017-01-01

The CREST reactive-burn model uses entropy-dependent reaction rates that, until now, have been manually tuned to fit shock-initiation and detonation data in hydrocode simulations. This paper describes the initial development of an automatic method for calibrating CREST reaction-rate coefficients, using particle swarm optimisation. The automatic method is applied to EDC32, to help develop the first CREST model for this conventional high explosive.

Fast and fuzzy multi-objective radiotherapy treatment plan generation for head and neck cancer patients with the lexicographic reference point method (LRPM)

NASA Astrophysics Data System (ADS)

van Haveren, Rens; Ogryczak, Włodzimierz; Verduijn, Gerda M.; Keijzer, Marleen; Heijmen, Ben J. M.; Breedveld, Sebastiaan

2017-06-01

Previously, we have proposed Erasmus-iCycle, an algorithm for fully automated IMRT plan generation based on prioritised (lexicographic) multi-objective optimisation with the 2-phase ɛ-constraint (2pɛc) method. For each patient, the output of Erasmus-iCycle is a clinically favourable, Pareto optimal plan. The 2pɛc method uses a list of objective functions that are consecutively optimised, following a strict, user-defined prioritisation. The novel lexicographic reference point method (LRPM) is capable of solving multi-objective problems in a single optimisation, using a fuzzy prioritisation of the objectives. Trade-offs are made globally, aiming for large favourable gains for lower prioritised objectives at the cost of only slight degradations for higher prioritised objectives, or vice versa. In this study, the LRPM is validated for 15 head and neck cancer patients receiving bilateral neck irradiation. The generated plans using the LRPM are compared with the plans resulting from the 2pɛc method. Both methods were capable of automatically generating clinically relevant treatment plans for all patients. For some patients, the LRPM allowed large favourable gains in some treatment plan objectives at the cost of only small degradations for the others. Moreover, because of the applied single optimisation instead of multiple optimisations, the LRPM reduced the average computation time from 209.2 to 9.5 min, a speed-up factor of 22 relative to the 2pɛc method.

Path integrals with higher order actions: Application to realistic chemical systems

NASA Astrophysics Data System (ADS)

Lindoy, Lachlan P.; Huang, Gavin S.; Jordan, Meredith J. T.

2018-02-01

Quantum thermodynamic parameters can be determined using path integral Monte Carlo (PIMC) simulations. These simulations, however, become computationally demanding as the quantum nature of the system increases, although their efficiency can be improved by using higher order approximations to the thermal density matrix, specifically the action. Here we compare the standard, primitive approximation to the action (PA) and three higher order approximations, the Takahashi-Imada action (TIA), the Suzuki-Chin action (SCA) and the Chin action (CA). The resulting PIMC methods are applied to two realistic potential energy surfaces, for H2O and HCN-HNC, both of which are spectroscopically accurate and contain three-body interactions. We further numerically optimise, for each potential, the SCA parameter and the two free parameters in the CA, obtaining more significant improvements in efficiency than seen previously in the literature. For both H2O and HCN-HNC, accounting for all required potential and force evaluations, the optimised CA formalism is approximately twice as efficient as the TIA formalism and approximately an order of magnitude more efficient than the PA. The optimised SCA formalism shows similar efficiency gains to the CA for HCN-HNC but has similar efficiency to the TIA for H2O at low temperature. In H2O and HCN-HNC systems, the optimal value of the a1 CA parameter is approximately 1/3 , corresponding to an equal weighting of all force terms in the thermal density matrix, and similar to previous studies, the optimal α parameter in the SCA was ˜0.31. Importantly, poor choice of parameter significantly degrades the performance of the SCA and CA methods. In particular, for the CA, setting a1 = 0 is not efficient: the reduction in convergence efficiency is not offset by the lower number of force evaluations. We also find that the harmonic approximation to the CA parameters, whilst providing a fourth order approximation to the action, is not optimal for these realistic potentials: numerical optimisation leads to better approximate cancellation of the fifth order terms, with deviation between the harmonic and numerically optimised parameters more marked in the more quantum H2O system. This suggests that numerically optimising the CA or SCA parameters, which can be done at high temperature, will be important in fully realising the efficiency gains of these formalisms for realistic potentials.

On the importance of appropriate precipitation gauge catch correction for hydrological modelling at mid to high latitudes

NASA Astrophysics Data System (ADS)

Stisen, S.; Højberg, A. L.; Troldborg, L.; Refsgaard, J. C.; Christensen, B. S. B.; Olsen, M.; Henriksen, H. J.

2012-11-01

Precipitation gauge catch correction is often given very little attention in hydrological modelling compared to model parameter calibration. This is critical because significant precipitation biases often make the calibration exercise pointless, especially when supposedly physically-based models are in play. This study addresses the general importance of appropriate precipitation catch correction through a detailed modelling exercise. An existing precipitation gauge catch correction method addressing solid and liquid precipitation is applied, both as national mean monthly correction factors based on a historic 30 yr record and as gridded daily correction factors based on local daily observations of wind speed and temperature. The two methods, named the historic mean monthly (HMM) and the time-space variable (TSV) correction, resulted in different winter precipitation rates for the period 1990-2010. The resulting precipitation datasets were evaluated through the comprehensive Danish National Water Resources model (DK-Model), revealing major differences in both model performance and optimised model parameter sets. Simulated stream discharge is improved significantly when introducing the TSV correction, whereas the simulated hydraulic heads and multi-annual water balances performed similarly due to recalibration adjusting model parameters to compensate for input biases. The resulting optimised model parameters are much more physically plausible for the model based on the TSV correction of precipitation. A proxy-basin test where calibrated DK-Model parameters were transferred to another region without site specific calibration showed better performance for parameter values based on the TSV correction. Similarly, the performances of the TSV correction method were superior when considering two single years with a much dryer and a much wetter winter, respectively, as compared to the winters in the calibration period (differential split-sample tests). We conclude that TSV precipitation correction should be carried out for studies requiring a sound dynamic description of hydrological processes, and it is of particular importance when using hydrological models to make predictions for future climates when the snow/rain composition will differ from the past climate. This conclusion is expected to be applicable for mid to high latitudes, especially in coastal climates where winter precipitation types (solid/liquid) fluctuate significantly, causing climatological mean correction factors to be inadequate.

Optimisation of GaN LEDs and the reduction of efficiency droop using active machine learning

DOE PAGES

Rouet-Leduc, Bertrand; Barros, Kipton Marcos; Lookman, Turab; ...

2016-04-26

A fundamental challenge in the design of LEDs is to maximise electro-luminescence efficiency at high current densities. We simulate GaN-based LED structures that delay the onset of efficiency droop by spreading carrier concentrations evenly across the active region. Statistical analysis and machine learning effectively guide the selection of the next LED structure to be examined based upon its expected efficiency as well as model uncertainty. This active learning strategy rapidly constructs a model that predicts Poisson-Schrödinger simulations of devices, and that simultaneously produces structures with higher simulated efficiencies.

Analysis and simulation of wireless signal propagation applying geostatistical interpolation techniques

NASA Astrophysics Data System (ADS)

Kolyaie, S.; Yaghooti, M.; Majidi, G.

2011-12-01

This paper is a part of an ongoing research to examine the capability of geostatistical analysis for mobile networks coverage prediction, simulation and tuning. Mobile network coverage predictions are used to find network coverage gaps and areas with poor serviceability. They are essential data for engineering and management in order to make better decision regarding rollout, planning and optimisation of mobile networks.The objective of this research is to evaluate different interpolation techniques in coverage prediction. In method presented here, raw data collected from drive testing a sample of roads in study area is analysed and various continuous surfaces are created using different interpolation methods. Two general interpolation methods are used in this paper with different variables; first, Inverse Distance Weighting (IDW) with various powers and number of neighbours and second, ordinary kriging with Gaussian, spherical, circular and exponential semivariogram models with different number of neighbours. For the result comparison, we have used check points coming from the same drive test data. Prediction values for check points are extracted from each surface and the differences with actual value are computed. The output of this research helps finding an optimised and accurate model for coverage prediction.

A new bio-inspired optimisation algorithm: Bird Swarm Algorithm

NASA Astrophysics Data System (ADS)

Meng, Xian-Bing; Gao, X. Z.; Lu, Lihua; Liu, Yu; Zhang, Hengzhen

2016-07-01

A new bio-inspired algorithm, namely Bird Swarm Algorithm (BSA), is proposed for solving optimisation applications. BSA is based on the swarm intelligence extracted from the social behaviours and social interactions in bird swarms. Birds mainly have three kinds of behaviours: foraging behaviour, vigilance behaviour and flight behaviour. Birds may forage for food and escape from the predators by the social interactions to obtain a high chance of survival. By modelling these social behaviours, social interactions and the related swarm intelligence, four search strategies associated with five simplified rules are formulated in BSA. Simulations and comparisons based on eighteen benchmark problems demonstrate the effectiveness, superiority and stability of BSA. Some proposals for future research about BSA are also discussed.

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

NASA Astrophysics Data System (ADS)

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.

Achieving optimal SERS through enhanced experimental design

PubMed Central

Fisk, Heidi; Westley, Chloe; Turner, Nicholas J.

2016-01-01

One of the current limitations surrounding surface‐enhanced Raman scattering (SERS) is the perceived lack of reproducibility. SERS is indeed challenging, and for analyte detection, it is vital that the analyte interacts with the metal surface. However, as this is analyte dependent, there is not a single set of SERS conditions that are universal. This means that experimental optimisation for optimum SERS response is vital. Most researchers optimise one factor at a time, where a single parameter is altered first before going onto optimise the next. This is a very inefficient way of searching the experimental landscape. In this review, we explore the use of more powerful multivariate approaches to SERS experimental optimisation based on design of experiments and evolutionary computational methods. We particularly focus on colloidal‐based SERS rather than thin film preparations as a result of their popularity. © 2015 The Authors. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd. PMID:27587905

Achieving optimal SERS through enhanced experimental design.

PubMed

Fisk, Heidi; Westley, Chloe; Turner, Nicholas J; Goodacre, Royston

2016-01-01

One of the current limitations surrounding surface-enhanced Raman scattering (SERS) is the perceived lack of reproducibility. SERS is indeed challenging, and for analyte detection, it is vital that the analyte interacts with the metal surface. However, as this is analyte dependent, there is not a single set of SERS conditions that are universal. This means that experimental optimisation for optimum SERS response is vital. Most researchers optimise one factor at a time, where a single parameter is altered first before going onto optimise the next. This is a very inefficient way of searching the experimental landscape. In this review, we explore the use of more powerful multivariate approaches to SERS experimental optimisation based on design of experiments and evolutionary computational methods. We particularly focus on colloidal-based SERS rather than thin film preparations as a result of their popularity. © 2015 The Authors. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd.

An analytical fuzzy-based approach to ?-gain optimal control of input-affine nonlinear systems using Newton-type algorithm

NASA Astrophysics Data System (ADS)

Milic, Vladimir; Kasac, Josip; Novakovic, Branko

2015-10-01

This paper is concerned with ?-gain optimisation of input-affine nonlinear systems controlled by analytic fuzzy logic system. Unlike the conventional fuzzy-based strategies, the non-conventional analytic fuzzy control method does not require an explicit fuzzy rule base. As the first contribution of this paper, we prove, by using the Stone-Weierstrass theorem, that the proposed fuzzy system without rule base is universal approximator. The second contribution of this paper is an algorithm for solving a finite-horizon minimax problem for ?-gain optimisation. The proposed algorithm consists of recursive chain rule for first- and second-order derivatives, Newton's method, multi-step Adams method and automatic differentiation. Finally, the results of this paper are evaluated on a second-order nonlinear system.

A simulation and optimisation procedure to model daily suppression resource transfers during a fire season in Colorado

Treesearch

Yu Wei; Erin J. Belval; Matthew P. Thompson; Dave E. Calkin; Crystal S. Stonesifer

2016-01-01

Sharing fire engines and crews between fire suppression dispatch zones may help improve the utilisation of fire suppression resources. Using the Resource Ordering and Status System, the Predictive Services’ Fire Potential Outlooks and the Rocky Mountain Region Preparedness Levels from 2010 to 2013, we tested a simulation and optimisation procedure to transfer crews and...

Optimising Service Delivery of AAC AT Devices and Compensating AT for Dyslexia.

PubMed

Roentgen, Uta R; Hagedoren, Edith A V; Horions, Katrien D L; Dalemans, Ruth J P

2017-01-01

To promote successful use of Assistive Technology (AT) supporting Augmentative and Alternative Communication (AAC) and compensating for dyslexia, the last steps of their provision, delivery and instruction, use, maintenance and evaluation, were optimised. In co-creation with all stakeholders based on a list of requirements an integral method and tools were developed.

Design and performance evaluation of a simplified dynamic model for combined sewer overflows in pumped sewer systems

NASA Astrophysics Data System (ADS)

van Daal-Rombouts, Petra; Sun, Siao; Langeveld, Jeroen; Bertrand-Krajewski, Jean-Luc; Clemens, François

2016-07-01

Optimisation or real time control (RTC) studies in wastewater systems increasingly require rapid simulations of sewer systems in extensive catchments. To reduce the simulation time calibrated simplified models are applied, with the performance generally based on the goodness of fit of the calibration. In this research the performance of three simplified and a full hydrodynamic (FH) model for two catchments are compared based on the correct determination of CSO event occurrences and of the total discharged volumes to the surface water. Simplified model M1 consists of a rainfall runoff outflow (RRO) model only. M2 combines the RRO model with a static reservoir model for the sewer behaviour. M3 comprises the RRO model and a dynamic reservoir model. The dynamic reservoir characteristics were derived from FH model simulations. It was found that M2 and M3 are able to describe the sewer behaviour of the catchments, contrary to M1. The preferred model structure depends on the quality of the information (geometrical database and monitoring data) available for the design and calibration of the model. Finally, calibrated simplified models are shown to be preferable to uncalibrated FH models when performing optimisation or RTC studies.

Automated model optimisation using the Cylc workflow engine (Cyclops v1.0)

NASA Astrophysics Data System (ADS)

Gorman, Richard M.; Oliver, Hilary J.

2018-06-01

Most geophysical models include many parameters that are not fully determined by theory, and can be tuned to improve the model's agreement with available data. We might attempt to automate this tuning process in an objective way by employing an optimisation algorithm to find the set of parameters that minimises a cost function derived from comparing model outputs with measurements. A number of algorithms are available for solving optimisation problems, in various programming languages, but interfacing such software to a complex geophysical model simulation presents certain challenges. To tackle this problem, we have developed an optimisation suite (Cyclops) based on the Cylc workflow engine that implements a wide selection of optimisation algorithms from the NLopt Python toolbox (Johnson, 2014). The Cyclops optimisation suite can be used to calibrate any modelling system that has itself been implemented as a (separate) Cylc model suite, provided it includes computation and output of the desired scalar cost function. A growing number of institutions are using Cylc to orchestrate complex distributed suites of interdependent cycling tasks within their operational forecast systems, and in such cases application of the optimisation suite is particularly straightforward. As a test case, we applied the Cyclops to calibrate a global implementation of the WAVEWATCH III (v4.18) third-generation spectral wave model, forced by ERA-Interim input fields. This was calibrated over a 1-year period (1997), before applying the calibrated model to a full (1979-2016) wave hindcast. The chosen error metric was the spatial average of the root mean square error of hindcast significant wave height compared with collocated altimeter records. We describe the results of a calibration in which up to 19 parameters were optimised.

Real time control of a combined sewer system using radar-measured precipitation--results of the pilot study.

PubMed

Petruck, A; Holtmeier, E; Redder, A; Teichgräber, B

2003-01-01

Emschergenossenschaft and Lippeverband have developed a method to use radar-measured precipitation as an input for a real-time control of a combined sewer system containing several overflow structures. Two real-time control strategies have been developed and tested, one is solely volume-based, the other is volume and pollution-based. The system has been implemented in a pilot study in Gelsenkirchen, Germany. During the project the system was optimised and is now in constant operation. It was found, that the volume of combined sewage overflow could be reduced by 5 per cent per year. This was also found in simulations carried out in similar catchment areas. Most of the potential of improvement can already be achieved by local pollution-based control strategies.

Optimisation of confinement in a fusion reactor using a nonlinear turbulence model

NASA Astrophysics Data System (ADS)

Highcock, E. G.; Mandell, N. R.; Barnes, M.

2018-04-01

The confinement of heat in the core of a magnetic fusion reactor is optimised using a multidimensional optimisation algorithm. For the first time in such a study, the loss of heat due to turbulence is modelled at every stage using first-principles nonlinear simulations which accurately capture the turbulent cascade and large-scale zonal flows. The simulations utilise a novel approach, with gyrofluid treatment of the small-scale drift waves and gyrokinetic treatment of the large-scale zonal flows. A simple near-circular equilibrium with standard parameters is chosen as the initial condition. The figure of merit, fusion power per unit volume, is calculated, and then two control parameters, the elongation and triangularity of the outer flux surface, are varied, with the algorithm seeking to optimise the chosen figure of merit. A twofold increase in the plasma power per unit volume is achieved by moving to higher elongation and strongly negative triangularity.

Fast Simulations of Gas Sloshing and Cold Front Formation

NASA Technical Reports Server (NTRS)

Roediger, E.; ZuHone, J. A.

2011-01-01

We present a simplified and fast method for simulating minor mergers between galaxy clusters. Instead of following the evolution of the dark matter halos directly by the N-body method, we employ a rigid potential approximation for both clusters. The simulations are run in the rest frame of the more massive cluster and account for the resulting inertial accelerations in an optimised way. We test the reliability of this method for studies of minor merger induced gas sloshing by performing a one-to-one comparison between our simulations and hydro+N-body ones. We find that the rigid potential approximation reproduces the sloshing-related features well except for two artefacts: the temperature just outside the cold fronts is slightly over-predicted, and the outward motion of the cold fronts is delayed by typically 200 Myr. We discuss reasons for both artefacts.

Fast Simulations of Gas Sloshing and Cold Front Formation

NASA Technical Reports Server (NTRS)

Roediger, E.; ZuHone, J. A.

2012-01-01

We present a simplified and fast method for simulating minor mergers between galaxy clusters. Instead of following the evolution of the dark matter halos directly by the N-body method, we employ a rigid potential approximation for both clusters. The simulations are run in the rest frame of the more massive cluster and account for the resulting inertial accelerations in an optimised way. We test the reliability of this method for studies of minor merger induced gas sloshing by performing a one-to-one comparison between our simulations and hydro+N-body ones. We find that the rigid potential approximation reproduces the sloshing-related features well except for two artifacts: the temperature just outside the cold fronts is slightly over-predicted, and the outward motion of the cold fronts is delayed by typically 200 Myr. We discuss reasons for both artifacts.

Optimised in vitro applicable loads for the simulation of lateral bending in the lumbar spine.

PubMed

Dreischarf, Marcel; Rohlmann, Antonius; Bergmann, Georg; Zander, Thomas

2012-07-01

In in vitro studies of the lumbar spine simplified loading modes (compressive follower force, pure moment) are usually employed to simulate the standard load cases flexion-extension, axial rotation and lateral bending of the upper body. However, the magnitudes of these loads vary widely in the literature. Thus the results of current studies may lead to unrealistic values and are hardly comparable. It is still unknown which load magnitudes lead to a realistic simulation of maximum lateral bending. A validated finite element model of the lumbar spine was used in an optimisation study to determine which magnitudes of the compressive follower force and bending moment deliver results that fit best with averaged in vivo data. The best agreement with averaged in vivo measured data was found for a compressive follower force of 700 N and a lateral bending moment of 7.8 Nm. These results show that loading modes that differ strongly from the optimised one may not realistically simulate maximum lateral bending. The simplified but in vitro applicable loading cannot perfectly mimic the in vivo situation. However, the optimised magnitudes are those which agree best with averaged in vivo measured data. Its consequent application would lead to a better comparability of different investigations. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

Battery Cell Balancing Optimisation for Battery Management System

NASA Astrophysics Data System (ADS)

Yusof, M. S.; Toha, S. F.; Kamisan, N. A.; Hashim, N. N. W. N.; Abdullah, M. A.

2017-03-01

Battery cell balancing in every electrical component such as home electronic equipment and electric vehicle is very important to extend battery run time which is simplified known as battery life. The underlying solution to equalize the balance of cell voltage and SOC between the cells when they are in complete charge. In order to control and extend the battery life, the battery cell balancing is design and manipulated in such way as well as shorten the charging process. Active and passive cell balancing strategies as a unique hallmark enables the balancing of the battery with the excellent performances configuration so that the charging process will be faster. The experimental and simulation covers an analysis of how fast the battery can balance for certain time. The simulation based analysis is conducted to certify the use of optimisation in active or passive cell balancing to extend battery life for long periods of time.

Design of distributed PID-type dynamic matrix controller for fractional-order systems

NASA Astrophysics Data System (ADS)

Wang, Dawei; Zhang, Ridong

2018-01-01

With the continuous requirements for product quality and safety operation in industrial production, it is difficult to describe the complex large-scale processes with integer-order differential equations. However, the fractional differential equations may precisely represent the intrinsic characteristics of such systems. In this paper, a distributed PID-type dynamic matrix control method based on fractional-order systems is proposed. First, the high-order approximate model of integer order is obtained by utilising the Oustaloup method. Then, the step response model vectors of the plant is obtained on the basis of the high-order model, and the online optimisation for multivariable processes is transformed into the optimisation of each small-scale subsystem that is regarded as a sub-plant controlled in the distributed framework. Furthermore, the PID operator is introduced into the performance index of each subsystem and the fractional-order PID-type dynamic matrix controller is designed based on Nash optimisation strategy. The information exchange among the subsystems is realised through the distributed control structure so as to complete the optimisation task of the whole large-scale system. Finally, the control performance of the designed controller in this paper is verified by an example.

Dynamic least-cost optimisation of wastewater system remedial works requirements.

PubMed

Vojinovic, Z; Solomatine, D; Price, R K

2006-01-01

In recent years, there has been increasing concern for wastewater system failure and identification of optimal set of remedial works requirements. So far, several methodologies have been developed and applied in asset management activities by various water companies worldwide, but often with limited success. In order to fill the gap, there are several research projects that have been undertaken in exploring various algorithms to optimise remedial works requirements, but mostly for drinking water supply systems, and very limited work has been carried out for the wastewater assets. Some of the major deficiencies of commonly used methods can be found in either one or more of the following aspects: inadequate representation of systems complexity, incorporation of a dynamic model into the decision-making loop, the choice of an appropriate optimisation technique and experience in applying that technique. This paper is oriented towards resolving these issues and discusses a new approach for the optimisation of wastewater systems remedial works requirements. It is proposed that the optimal problem search is performed by a global optimisation tool (with various random search algorithms) and the system performance is simulated by the hydrodynamic pipe network model. The work on assembling all required elements and the development of an appropriate interface protocols between the two tools, aimed to decode the potential remedial solutions into the pipe network model and to calculate the corresponding scenario costs, is currently underway.

Multi-objective ACO algorithms to minimise the makespan and the total rejection cost on BPMs with arbitrary job weights

NASA Astrophysics Data System (ADS)

Jia, Zhao-hong; Pei, Ming-li; Leung, Joseph Y.-T.

2017-12-01

In this paper, we investigate the batch-scheduling problem with rejection on parallel machines with non-identical job sizes and arbitrary job-rejected weights. If a job is rejected, the corresponding penalty has to be paid. Our objective is to minimise the makespan of the processed jobs and the total rejection cost of the rejected jobs. Based on the selected multi-objective optimisation approaches, two problems, P1 and P2, are considered. In P1, the two objectives are linearly combined into one single objective. In P2, the two objectives are simultaneously minimised and the Pareto non-dominated solution set is to be found. Based on the ant colony optimisation (ACO), two algorithms, called LACO and PACO, are proposed to address the two problems, respectively. Two different objective-oriented pheromone matrices and heuristic information are designed. Additionally, a local optimisation algorithm is adopted to improve the solution quality. Finally, simulated experiments are conducted, and the comparative results verify the effectiveness and efficiency of the proposed algorithms, especially on large-scale instances.

Thermodynamic properties of solvated peptides from selective integrated tempering sampling with a new weighting factor estimation algorithm

NASA Astrophysics Data System (ADS)

Shen, Lin; Xie, Liangxu; Yang, Mingjun

2017-04-01

Conformational sampling under rugged energy landscape is always a challenge in computer simulations. The recently developed integrated tempering sampling, together with its selective variant (SITS), emerges to be a powerful tool in exploring the free energy landscape or functional motions of various systems. The estimation of weighting factors constitutes a critical step in these methods and requires accurate calculation of partition function ratio between different thermodynamic states. In this work, we propose a new adaptive update algorithm to compute the weighting factors based on the weighted histogram analysis method (WHAM). The adaptive-WHAM algorithm with SITS is then applied to study the thermodynamic properties of several representative peptide systems solvated in an explicit water box. The performance of the new algorithm is validated in simulations of these solvated peptide systems. We anticipate more applications of this coupled optimisation and production algorithm to other complicated systems such as the biochemical reactions in solution.

Simulation of geothermal water extraction in heterogeneous reservoirs using dynamic unstructured mesh optimisation

NASA Astrophysics Data System (ADS)

Salinas, P.; Pavlidis, D.; Jacquemyn, C.; Lei, Q.; Xie, Z.; Pain, C.; Jackson, M.

2017-12-01

It is well known that the pressure gradient into a production well increases with decreasing distance to the well. To properly capture the local pressure drawdown into the well a high grid or mesh resolution is required; moreover, the location of the well must be captured accurately. In conventional simulation models, the user must interact with the model to modify grid resolution around wells of interest, and the well location is approximated on a grid defined early in the modelling process.We report a new approach for improved simulation of near wellbore flow in reservoir scale models through the use of dynamic mesh optimisation and the recently presented double control volume finite element method. Time is discretized using an adaptive, implicit approach. Heterogeneous geologic features are represented as volumes bounded by surfaces. Within these volumes, termed geologic domains, the material properties are constant. Up-, cross- or down-scaling of material properties during dynamic mesh optimization is not required, as the properties are uniform within each geologic domain. A given model typically contains numerous such geologic domains. Wells are implicitly coupled with the domain, and the fluid flows is modelled inside the wells. The method is novel for two reasons. First, a fully unstructured tetrahedral mesh is used to discretize space, and the spatial location of the well is specified via a line vector, ensuring its location even if the mesh is modified during the simulation. The well location is therefore accurately captured, the approach allows complex well trajectories and wells with many laterals to be modelled. Second, computational efficiency is increased by use of dynamic mesh optimization, in which an unstructured mesh adapts in space and time to key solution fields (preserving the geometry of the geologic domains), such as pressure, velocity or temperature, this also increases the quality of the solutions by placing higher resolution where required to reduce an error metric based on the Hessian of the field. This allows the local pressure drawdown to be captured without user¬ driven modification of the mesh. We demonstrate that the method has wide application in reservoir ¬scale models of geothermal fields, and regional models of groundwater resources.

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

NASA Astrophysics Data System (ADS)

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.

Data-driven train set crash dynamics simulation

NASA Astrophysics Data System (ADS)

Tang, Zhao; Zhu, Yunrui; Nie, Yinyu; Guo, Shihui; Liu, Fengjia; Chang, Jian; Zhang, Jianjun

2017-02-01

Traditional finite element (FE) methods are arguably expensive in computation/simulation of the train crash. High computational cost limits their direct applications in investigating dynamic behaviours of an entire train set for crashworthiness design and structural optimisation. On the contrary, multi-body modelling is widely used because of its low computational cost with the trade-off in accuracy. In this study, a data-driven train crash modelling method is proposed to improve the performance of a multi-body dynamics simulation of train set crash without increasing the computational burden. This is achieved by the parallel random forest algorithm, which is a machine learning approach that extracts useful patterns of force-displacement curves and predicts a force-displacement relation in a given collision condition from a collection of offline FE simulation data on various collision conditions, namely different crash velocities in our analysis. Using the FE simulation results as a benchmark, we compared our method with traditional multi-body modelling methods and the result shows that our data-driven method improves the accuracy over traditional multi-body models in train crash simulation and runs at the same level of efficiency.

BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience.

PubMed

Van Geit, Werner; Gevaert, Michael; Chindemi, Giuseppe; Rössert, Christian; Courcol, Jean-Denis; Muller, Eilif B; Schürmann, Felix; Segev, Idan; Markram, Henry

2016-01-01

At many scales in neuroscience, appropriate mathematical models take the form of complex dynamical systems. Parameterizing such models to conform to the multitude of available experimental constraints is a global non-linear optimisation problem with a complex fitness landscape, requiring numerical techniques to find suitable approximate solutions. Stochastic optimisation approaches, such as evolutionary algorithms, have been shown to be effective, but often the setting up of such optimisations and the choice of a specific search algorithm and its parameters is non-trivial, requiring domain-specific expertise. Here we describe BluePyOpt, a Python package targeted at the broad neuroscience community to simplify this task. BluePyOpt is an extensible framework for data-driven model parameter optimisation that wraps and standardizes several existing open-source tools. It simplifies the task of creating and sharing these optimisations, and the associated techniques and knowledge. This is achieved by abstracting the optimisation and evaluation tasks into various reusable and flexible discrete elements according to established best-practices. Further, BluePyOpt provides methods for setting up both small- and large-scale optimisations on a variety of platforms, ranging from laptops to Linux clusters and cloud-based compute infrastructures. The versatility of the BluePyOpt framework is demonstrated by working through three representative neuroscience specific use cases.

An improved predictive functional control method with application to PMSM systems

NASA Astrophysics Data System (ADS)

Li, Shihua; Liu, Huixian; Fu, Wenshu

2017-01-01

In common design of prediction model-based control method, usually disturbances are not considered in the prediction model as well as the control design. For the control systems with large amplitude or strong disturbances, it is difficult to precisely predict the future outputs according to the conventional prediction model, and thus the desired optimal closed-loop performance will be degraded to some extent. To this end, an improved predictive functional control (PFC) method is developed in this paper by embedding disturbance information into the system model. Here, a composite prediction model is thus obtained by embedding the estimated value of disturbances, where disturbance observer (DOB) is employed to estimate the lumped disturbances. So the influence of disturbances on system is taken into account in optimisation procedure. Finally, considering the speed control problem for permanent magnet synchronous motor (PMSM) servo system, a control scheme based on the improved PFC method is designed to ensure an optimal closed-loop performance even in the presence of disturbances. Simulation and experimental results based on a hardware platform are provided to confirm the effectiveness of the proposed algorithm.

Analysis of dynamic cerebral autoregulation using an ARX model based on arterial blood pressure and middle cerebral artery velocity simulation.

PubMed

Liu, Y; Allen, R

2002-09-01

The study aimed to model the cerebrovascular system, using a linear ARX model based on data simulated by a comprehensive physiological model, and to assess the range of applicability of linear parametric models. Arterial blood pressure (ABP) and middle cerebral arterial blood flow velocity (MCAV) were measured from 11 subjects non-invasively, following step changes in ABP, using the thigh cuff technique. By optimising parameters associated with autoregulation, using a non-linear optimisation technique, the physiological model showed a good performance (r=0.83+/-0.14) in fitting MCAV. An additional five sets of measured ABP of length 236+/-154 s were acquired from a subject at rest. These were normalised and rescaled to coefficients of variation (CV=SD/mean) of 2% and 10% for model comparisons. Randomly generated Gaussian noise with standard deviation (SD) from 1% to 5% was added to both ABP and physiologically simulated MCAV (SMCAV), with 'normal' and 'impaired' cerebral autoregulation, to simulate the real measurement conditions. ABP and SMCAV were fitted by ARX modelling, and cerebral autoregulation was quantified by a 5 s recovery percentage R5% of the step responses of the ARX models. The study suggests that cerebral autoregulation can be assessed by computing the R5% of the step response of an ARX model of appropriate order, even when measurement noise is considerable.

Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates

NASA Astrophysics Data System (ADS)

Todorovic, Andrijana; Plavsic, Jasna

2015-04-01

A conceptual rainfall-runoff model is defined by its structure and parameters, which are commonly inferred through model calibration. Parameter estimates depend on objective function(s), optimisation method, and calibration period. Model calibration over different periods may result in dissimilar parameter estimates, while model efficiency decreases outside calibration period. Problem of model (parameter) transferability, which conditions reliability of hydrologic simulations, has been investigated for decades. In this paper, dependence of the parameter estimates and model performance on calibration period is analysed. The main question that is addressed is: are there any changes in optimised parameters and model efficiency that can be linked to the changes in hydrologic or meteorological variables (flow, precipitation and temperature)? Conceptual, semi-distributed HBV-light model is calibrated over five-year periods shifted by a year (sliding time windows). Length of the calibration periods is selected to enable identification of all parameters. One water year of model warm-up precedes every simulation, which starts with the beginning of a water year. The model is calibrated using the built-in GAP optimisation algorithm. The objective function used for calibration is composed of Nash-Sutcliffe coefficient for flows and logarithms of flows, and volumetric error, all of which participate in the composite objective function with approximately equal weights. Same prior parameter ranges are used in all simulations. The model is calibrated against flows observed at the Slovac stream gauge on the Kolubara River in Serbia (records from 1954 to 2013). There are no trends in precipitation nor in flows, however, there is a statistically significant increasing trend in temperatures at this catchment. Parameter variability across the calibration periods is quantified in terms of standard deviations of normalised parameters, enabling detection of the most variable parameters. Correlation coefficients among optimised model parameters and total precipitation P, mean temperature T and mean flow Q are calculated to give an insight into parameter dependence on the hydrometeorological drivers. The results reveal high sensitivity of almost all model parameters towards calibration period. The highest variability is displayed by the refreezing coefficient, water holding capacity, and temperature gradient. The only statistically significant (decreasing) trend is detected in the evapotranspiration reduction threshold. Statistically significant correlation is detected between the precipitation gradient and precipitation depth, and between the time-area histogram base and flows. All other correlations are not statistically significant, implying that changes in optimised parameters cannot generally be linked to the changes in P, T or Q. As for the model performance, the model reproduces the observed runoff satisfactorily, though the runoff is slightly overestimated in wet periods. The Nash-Sutcliffe efficiency coefficient (NSE) ranges from 0.44 to 0.79. Higher NSE values are obtained over wetter periods, what is supported by statistically significant correlation between NSE and flows. Overall, no systematic variations in parameters or in model performance are detected. Parameter variability may therefore rather be attributed to errors in data or inadequacies in the model structure. Further research is required to examine the impact of the calibration strategy or model structure on the variability in optimised parameters in time.

Optimisation of substrate blends in anaerobic co-digestion using adaptive linear programming.

PubMed

García-Gen, Santiago; Rodríguez, Jorge; Lema, Juan M

2014-12-01

Anaerobic co-digestion of multiple substrates has the potential to enhance biogas productivity by making use of the complementary characteristics of different substrates. A blending strategy based on a linear programming optimisation method is proposed aiming at maximising COD conversion into methane, but simultaneously maintaining a digestate and biogas quality. The method incorporates experimental and heuristic information to define the objective function and the linear restrictions. The active constraints are continuously adapted (by relaxing the restriction boundaries) such that further optimisations in terms of methane productivity can be achieved. The feasibility of the blends calculated with this methodology was previously tested and accurately predicted with an ADM1-based co-digestion model. This was validated in a continuously operated pilot plant, treating for several months different mixtures of glycerine, gelatine and pig manure at organic loading rates from 1.50 to 4.93 gCOD/Ld and hydraulic retention times between 32 and 40 days at mesophilic conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Design and experimental analysis of a new malleovestibulopexy prosthesis using a finite element model of the human middle ear.

PubMed

Vallejo Valdezate, Luis A; Hidalgo Otamendi, Antonio; Hernández, Alberto; Lobo, Fernando; Gil-Carcedo Sañudo, Elisa; Gil-Carcedo García, Luis M

2015-01-01

Many designs of prostheses are available for middle ear surgery. In this study we propose a design for a new prosthesis, which optimises mechanical performance in the human middle ear and improves some deficiencies in the prostheses currently available. Our objective was to design and assess the theoretical acoustic-mechanical behaviour of this new total ossicular replacement prosthesis. The design of this new prosthesis was based on an animal model (an iguana). For the modelling and mechanical analysis of the new prosthesis, we used a dynamic 3D computer model of the human middle ear, based on the finite elements method (FEM). The new malleovestibulopexy prosthesis design demonstrates an acoustical-mechanical performance similar to that of the healthy human middle ear. This new design also has additional advantages, such as ease of implantation and stability in the middle ear. This study shows that computer simulation can be used to design and optimise the vibroacoustic characteristics of middle ear implants and demonstrates the effectiveness of a new malleovestibulopexy prosthesis in reconstructing the ossicular chain. Copyright © 2014 Elsevier España, S.L.U. y Sociedad Española de Otorrinolaringología y Patología Cérvico-Facial. All rights reserved.

Optimum design and operation of primary sludge fermentation schemes for volatile fatty acids production.

PubMed

Chanona, J; Ribes, J; Seco, A; Ferrer, J

2006-01-01

This paper presents a model-knowledge based algorithm for optimising the primary sludge fermentation process design and operation. This is a recently used method to obtain the volatile fatty acids (VFA), needed to improve biological nutrient removal processes, directly from the raw wastewater. The proposed algorithm consists in a heuristic reasoning algorithm based on the expert knowledge of the process. Only effluent VFA and the sludge blanket height (SBH) have to be set as design criteria, and the optimisation algorithm obtains the minimum return sludge and waste sludge flow rates which fulfil those design criteria. A pilot plant fed with municipal raw wastewater was operated in order to obtain experimental results supporting the developed algorithm groundwork. The experimental results indicate that when SBH was increased, higher solids retention time was obtained in the settler and VFA production increased. Higher recirculation flow-rates resulted in higher VFA production too. Finally, the developed algorithm has been tested by simulating different design conditions with very good results. It has been able to find the optimal operation conditions in all cases on which preset design conditions could be achieved. Furthermore, this is a general algorithm that can be applied to any fermentation-elutriation scheme with or without fermentation reactor.

Preoptimised VB: a fast method for the ground and excited states of ionic clusters I. Localised preoptimisation for (ArCO) +, (ArN 2) + and N 4+

NASA Astrophysics Data System (ADS)

Langenberg, J. H.; Bucur, I. B.; Archirel, P.

1997-09-01

We show that in the simple case of van der Waals ionic clusters, the optimisation of orbitals within VB can be easily simulated with the help of pseudopotentials. The procedure yields the ground and the first excited states of the cluster simultaneously. This makes the calculation of potential energy surfaces for tri- and tetraatomic clusters possible, with very acceptable computation times. We give potential curves for (ArCO) +, (ArN 2) + and N 4+. An application to the simulation of the SCF method is shown for Na +H 2O.

Satellite Vibration Testing: Angle optimisation method to Reduce Overtesting

NASA Astrophysics Data System (ADS)

Knight, Charly; Remedia, Marcello; Aglietti, Guglielmo S.; Richardson, Guy

2018-06-01

Spacecraft overtesting is a long running problem, and the main focus of most attempts to reduce it has been to adjust the base vibration input (i.e. notching). Instead this paper examines testing alternatives for secondary structures (equipment) coupled to the main structure (satellite) when they are tested separately. Even if the vibration source is applied along one of the orthogonal axes at the base of the coupled system (satellite plus equipment), the dynamics of the system and potentially the interface configuration mean the vibration at the interface may not occur all along one axis much less the corresponding orthogonal axis of the base excitation. This paper proposes an alternative testing methodology in which the testing of a piece of equipment occurs at an offset angle. This Angle Optimisation method may have multiple tests but each with an altered input direction allowing for the best match between all specified equipment system responses with coupled system tests. An optimisation process that compares the calculated equipment RMS values for a range of inputs with the maximum coupled system RMS values, and is used to find the optimal testing configuration for the given parameters. A case study was performed to find the best testing angles to match the acceleration responses of the centre of mass and sum of interface forces for all three axes, as well as the von Mises stress for an element by a fastening point. The angle optimisation method resulted in RMS values and PSD responses that were much closer to the coupled system when compared with traditional testing. The optimum testing configuration resulted in an overall average error significantly smaller than the traditional method. Crucially, this case study shows that the optimum test campaign could be a single equipment level test opposed to the traditional three orthogonal direction tests.

Scaling and kinematics optimisation of the scapula and thorax in upper limb musculoskeletal models

PubMed Central

Prinold, Joe A.I.; Bull, Anthony M.J.

2014-01-01

Accurate representation of individual scapula kinematics and subject geometries is vital in musculoskeletal models applied to upper limb pathology and performance. In applying individual kinematics to a model׳s cadaveric geometry, model constraints are commonly prescriptive. These rely on thorax scaling to effectively define the scapula׳s path but do not consider the area underneath the scapula in scaling, and assume a fixed conoid ligament length. These constraints may not allow continuous solutions or close agreement with directly measured kinematics. A novel method is presented to scale the thorax based on palpated scapula landmarks. The scapula and clavicle kinematics are optimised with the constraint that the scapula medial border does not penetrate the thorax. Conoid ligament length is not used as a constraint. This method is simulated in the UK National Shoulder Model and compared to four other methods, including the standard technique, during three pull-up techniques (n=11). These are high-performance activities covering a large range of motion. Model solutions without substantial jumps in the joint kinematics data were improved from 23% of trials with the standard method, to 100% of trials with the new method. Agreement with measured kinematics was significantly improved (more than 10° closer at p<0.001) when compared to standard methods. The removal of the conoid ligament constraint and the novel thorax scaling correction factor were shown to be key. Separation of the medial border of the scapula from the thorax was large, although this may be physiologically correct due to the high loads and high arm elevation angles. PMID:25011621

An integrated modelling and multicriteria analysis approach to managing nitrate diffuse pollution: 2. A case study for a chalk catchment in England.

PubMed

Koo, B K; O'Connell, P E

2006-04-01

The site-specific land use optimisation methodology, suggested by the authors in the first part of this two-part paper, has been applied to the River Kennet catchment at Marlborough, Wiltshire, UK, for a case study. The Marlborough catchment (143 km(2)) is an agriculture-dominated rural area over a deep chalk aquifer that is vulnerable to nitrate pollution from agricultural diffuse sources. For evaluation purposes, the catchment was discretised into a network of 1 kmx1 km grid cells. For each of the arable-land grid cells, seven land use alternatives (four arable-land alternatives and three grassland alternatives) were evaluated for their environmental and economic potential. For environmental evaluation, nitrate leaching rates of land use alternatives were estimated using SHETRAN simulations and groundwater pollution potential was evaluated using the DRASTIC index. For economic evaluation, economic gross margins were estimated using a simple agronomic model based on nitrogen response functions and agricultural land classification grades. In order to see whether the site-specific optimisation is efficient at the catchment scale, land use optimisation was carried out for four optimisation schemes (i.e. using four sets of criterion weights). Consequently, four land use scenarios were generated and the site-specifically optimised land use scenario was evaluated as the best compromise solution between long term nitrate pollution and agronomy at the catchment scale.

Refinement procedure for the image alignment in high-resolution electron tomography.

PubMed

Houben, L; Bar Sadan, M

2011-01-01

High-resolution electron tomography from a tilt series of transmission electron microscopy images requires an accurate image alignment procedure in order to maximise the resolution of the tomogram. This is the case in particular for ultra-high resolution where even very small misalignments between individual images can dramatically reduce the fidelity of the resultant reconstruction. A tomographic-reconstruction based and marker-free method is proposed, which uses an iterative optimisation of the tomogram resolution. The method utilises a search algorithm that maximises the contrast in tomogram sub-volumes. Unlike conventional cross-correlation analysis it provides the required correlation over a large tilt angle separation and guarantees a consistent alignment of images for the full range of object tilt angles. An assessment based on experimental reconstructions shows that the marker-free procedure is competitive to the reference of marker-based procedures at lower resolution and yields sub-pixel accuracy even for simulated high-resolution data. Copyright © 2011 Elsevier B.V. All rights reserved.

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

PubMed

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.

BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience

PubMed Central

Van Geit, Werner; Gevaert, Michael; Chindemi, Giuseppe; Rössert, Christian; Courcol, Jean-Denis; Muller, Eilif B.; Schürmann, Felix; Segev, Idan; Markram, Henry

2016-01-01

At many scales in neuroscience, appropriate mathematical models take the form of complex dynamical systems. Parameterizing such models to conform to the multitude of available experimental constraints is a global non-linear optimisation problem with a complex fitness landscape, requiring numerical techniques to find suitable approximate solutions. Stochastic optimisation approaches, such as evolutionary algorithms, have been shown to be effective, but often the setting up of such optimisations and the choice of a specific search algorithm and its parameters is non-trivial, requiring domain-specific expertise. Here we describe BluePyOpt, a Python package targeted at the broad neuroscience community to simplify this task. BluePyOpt is an extensible framework for data-driven model parameter optimisation that wraps and standardizes several existing open-source tools. It simplifies the task of creating and sharing these optimisations, and the associated techniques and knowledge. This is achieved by abstracting the optimisation and evaluation tasks into various reusable and flexible discrete elements according to established best-practices. Further, BluePyOpt provides methods for setting up both small- and large-scale optimisations on a variety of platforms, ranging from laptops to Linux clusters and cloud-based compute infrastructures. The versatility of the BluePyOpt framework is demonstrated by working through three representative neuroscience specific use cases. PMID:27375471

Discontinuous permeable adsorptive barrier design and cost analysis: a methodological approach to optimisation.

PubMed

Santonastaso, Giovanni Francesco; Bortone, Immacolata; Chianese, Simeone; Di Nardo, Armando; Di Natale, Michele; Erto, Alessandro; Karatza, Despina; Musmarra, Dino

2017-09-19

The following paper presents a method to optimise a discontinuous permeable adsorptive barrier (PAB-D). This method is based on the comparison of different PAB-D configurations obtained by changing some of the main PAB-D design parameters. In particular, the well diameters, the distance between two consecutive passive wells and the distance between two consecutive well lines were varied, and a cost analysis for each configuration was carried out in order to define the best performing and most cost-effective PAB-D configuration. As a case study, a benzene-contaminated aquifer located in an urban area in the north of Naples (Italy) was considered. The PAB-D configuration with a well diameter of 0.8 m resulted the best optimised layout in terms of performance and cost-effectiveness. Moreover, in order to identify the best configuration for the remediation of the aquifer studied, a comparison with a continuous permeable adsorptive barrier (PAB-C) was added. In particular, this showed a 40% reduction of the total remediation costs by using the optimised PAB-D.

Modelling the protocol stack in NCS with deterministic and stochastic petri net

NASA Astrophysics Data System (ADS)

Hui, Chen; Chunjie, Zhou; Weifeng, Zhu

2011-06-01

Protocol stack is the basis of the networked control systems (NCS). Full or partial reconfiguration of protocol stack offers both optimised communication service and system performance. Nowadays, field testing is unrealistic to determine the performance of reconfigurable protocol stack; and the Petri net formal description technique offers the best combination of intuitive representation, tool support and analytical capabilities. Traditionally, separation between the different layers of the OSI model has been a common practice. Nevertheless, such a layered modelling analysis framework of protocol stack leads to the lack of global optimisation for protocol reconfiguration. In this article, we proposed a general modelling analysis framework for NCS based on the cross-layer concept, which is to establish an efficiency system scheduling model through abstracting the time constraint, the task interrelation, the processor and the bus sub-models from upper and lower layers (application, data link and physical layer). Cross-layer design can help to overcome the inadequacy of global optimisation based on information sharing between protocol layers. To illustrate the framework, we take controller area network (CAN) as a case study. The simulation results of deterministic and stochastic Petri-net (DSPN) model can help us adjust the message scheduling scheme and obtain better system performance.

A Dynamic Finite Element Method for Simulating the Physics of Faults Systems

NASA Astrophysics Data System (ADS)

Saez, E.; Mora, P.; Gross, L.; Weatherley, D.

2004-12-01

We introduce a dynamic Finite Element method using a novel high level scripting language to describe the physical equations, boundary conditions and time integration scheme. The library we use is the parallel Finley library: a finite element kernel library, designed for solving large-scale problems. It is incorporated as a differential equation solver into a more general library called escript, based on the scripting language Python. This library has been developed to facilitate the rapid development of 3D parallel codes, and is optimised for the Australian Computational Earth Systems Simulator Major National Research Facility (ACcESS MNRF) supercomputer, a 208 processor SGI Altix with a peak performance of 1.1 TFlops. Using the scripting approach we obtain a parallel FE code able to take advantage of the computational efficiency of the Altix 3700. We consider faults as material discontinuities (the displacement, velocity, and acceleration fields are discontinuous at the fault), with elastic behavior. The stress continuity at the fault is achieved naturally through the expression of the fault interactions in the weak formulation. The elasticity problem is solved explicitly in time, using the Saint Verlat scheme. Finally, we specify a suitable frictional constitutive relation and numerical scheme to simulate fault behaviour. Our model is based on previous work on modelling fault friction and multi-fault systems using lattice solid-like models. We adapt the 2D model for simulating the dynamics of parallel fault systems described to the Finite-Element method. The approach uses a frictional relation along faults that is slip and slip-rate dependent, and the numerical integration approach introduced by Mora and Place in the lattice solid model. In order to illustrate the new Finite Element model, single and multi-fault simulation examples are presented.

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

NASA Astrophysics Data System (ADS)

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 that the best use of resources for the network design problem would be spent in improvement of the prior estimates of the flux uncertainties rather than investing these resources in running a complex evolutionary optimisation algorithm. The authors recommend that, if time and computational resources allow, that multiple optimisation techniques should be used as a part of a comprehensive suite of sensitivity tests when performing such an optimisation exercise. This will provide a selection of best solutions which could be ranked based on their utility and practicality.

An effective pseudospectral method for constraint dynamic optimisation problems with characteristic times

NASA Astrophysics Data System (ADS)

Xiao, Long; Liu, Xinggao; Ma, Liang; Zhang, Zeyin

2018-03-01

Dynamic optimisation problem with characteristic times, widely existing in many areas, is one of the frontiers and hotspots of dynamic optimisation researches. This paper considers a class of dynamic optimisation problems with constraints that depend on the interior points either fixed or variable, where a novel direct pseudospectral method using Legendre-Gauss (LG) collocation points for solving these problems is presented. The formula for the state at the terminal time of each subdomain is derived, which results in a linear combination of the state at the LG points in the subdomains so as to avoid the complex nonlinear integral. The sensitivities of the state at the collocation points with respect to the variable characteristic times are derived to improve the efficiency of the method. Three well-known characteristic time dynamic optimisation problems are solved and compared in detail among the reported literature methods. The research results show the effectiveness of the proposed method.

Metric optimisation for analogue forecasting by simulated annealing

NASA Astrophysics Data System (ADS)

Bliefernicht, J.; Bárdossy, A.

2009-04-01

It is well known that weather patterns tend to recur from time to time. This property of the atmosphere is used by analogue forecasting techniques. They have a long history in weather forecasting and there are many applications predicting hydrological variables at the local scale for different lead times. The basic idea of the technique is to identify past weather situations which are similar (analogue) to the predicted one and to take the local conditions of the analogues as forecast. But the forecast performance of the analogue method depends on user-defined criteria like the choice of the distance function and the size of the predictor domain. In this study we propose a new methodology of optimising both criteria by minimising the forecast error with simulated annealing. The performance of the methodology is demonstrated for the probability forecast of daily areal precipitation. It is compared with a traditional analogue forecasting algorithm, which is used operational as an element of a hydrological forecasting system. The study is performed for several meso-scale catchments located in the Rhine basin in Germany. The methodology is validated by a jack-knife method in a perfect prognosis framework for a period of 48 years (1958-2005). The predictor variables are derived from the NCEP/NCAR reanalysis data set. The Brier skill score and the economic value are determined to evaluate the forecast skill and value of the technique. In this presentation we will present the concept of the optimisation algorithm and the outcome of the comparison. It will be also demonstrated how a decision maker should apply a probability forecast to maximise the economic benefit from it.

The development and optimisation of 3D black-blood R2* mapping of the carotid artery wall.

PubMed

Yuan, Jianmin; Graves, Martin J; Patterson, Andrew J; Priest, Andrew N; Ruetten, Pascal P R; Usman, Ammara; Gillard, Jonathan H

2017-12-01

To develop and optimise a 3D black-blood R 2 * mapping sequence for imaging the carotid artery wall, using optimal blood suppression and k-space view ordering. Two different blood suppression preparation methods were used; Delay Alternating with Nutation for Tailored Excitation (DANTE) and improved Motion Sensitive Driven Equilibrium (iMSDE) were each combined with a three-dimensional (3D) multi-echo Fast Spoiled GRadient echo (ME-FSPGR) readout. Three different k-space view-order designs: Radial Fan-beam Encoding Ordering (RFEO), Distance-Determined Encoding Ordering (DDEO) and Centric Phase Encoding Order (CPEO) were investigated. The sequences were evaluated through Bloch simulation and in a cohort of twenty volunteers. The vessel wall Signal-to-Noise Ratio (SNR), Contrast-to-Noise Ratio (CNR) and R 2 *, and the sternocleidomastoid muscle R 2 * were measured and compared. Different numbers of acquisitions-per-shot (APS) were evaluated to further optimise the effectiveness of blood suppression. All sequences resulted in comparable R 2 * measurements to a conventional, i.e. non-blood suppressed sequence in the sternocleidomastoid muscle of the volunteers. Both Bloch simulations and volunteer data showed that DANTE has a higher signal intensity and results in a higher image SNR than iMSDE. Blood suppression efficiency was not significantly different when using different k-space view orders. Smaller APS achieved better blood suppression. The use of blood-suppression preparation methods does not affect the measurement of R 2 *. DANTE prepared ME-FSPGR sequence with a small number of acquisitions-per-shot can provide high quality black-blood R 2 * measurements of the carotid vessel wall. Copyright © 2017 Elsevier Inc. All rights reserved.

Topology Optimisation of Wideband Coaxial-to-Waveguide Transitions

NASA Astrophysics Data System (ADS)

Hassan, Emadeldeen; Noreland, Daniel; Wadbro, Eddie; Berggren, Martin

2017-03-01

To maximize the matching between a coaxial cable and rectangular waveguides, we present a computational topology optimisation approach that decides for each point in a given domain whether to hold a good conductor or a good dielectric. The conductivity is determined by a gradient-based optimisation method that relies on finite-difference time-domain solutions to the 3D Maxwell’s equations. Unlike previously reported results in the literature for this kind of problems, our design algorithm can efficiently handle tens of thousands of design variables that can allow novel conceptual waveguide designs. We demonstrate the effectiveness of the approach by presenting optimised transitions with reflection coefficients lower than -15 dB over more than a 60% bandwidth, both for right-angle and end-launcher configurations. The performance of the proposed transitions is cross-verified with a commercial software, and one design case is validated experimentally.

Topology Optimisation of Wideband Coaxial-to-Waveguide Transitions.

PubMed

Hassan, Emadeldeen; Noreland, Daniel; Wadbro, Eddie; Berggren, Martin

2017-03-23

To maximize the matching between a coaxial cable and rectangular waveguides, we present a computational topology optimisation approach that decides for each point in a given domain whether to hold a good conductor or a good dielectric. The conductivity is determined by a gradient-based optimisation method that relies on finite-difference time-domain solutions to the 3D Maxwell's equations. Unlike previously reported results in the literature for this kind of problems, our design algorithm can efficiently handle tens of thousands of design variables that can allow novel conceptual waveguide designs. We demonstrate the effectiveness of the approach by presenting optimised transitions with reflection coefficients lower than -15 dB over more than a 60% bandwidth, both for right-angle and end-launcher configurations. The performance of the proposed transitions is cross-verified with a commercial software, and one design case is validated experimentally.

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

NASA Astrophysics Data System (ADS)

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%.

Topology Optimisation of Wideband Coaxial-to-Waveguide Transitions

PubMed Central

Hassan, Emadeldeen; Noreland, Daniel; Wadbro, Eddie; Berggren, Martin

2017-01-01

To maximize the matching between a coaxial cable and rectangular waveguides, we present a computational topology optimisation approach that decides for each point in a given domain whether to hold a good conductor or a good dielectric. The conductivity is determined by a gradient-based optimisation method that relies on finite-difference time-domain solutions to the 3D Maxwell’s equations. Unlike previously reported results in the literature for this kind of problems, our design algorithm can efficiently handle tens of thousands of design variables that can allow novel conceptual waveguide designs. We demonstrate the effectiveness of the approach by presenting optimised transitions with reflection coefficients lower than −15 dB over more than a 60% bandwidth, both for right-angle and end-launcher configurations. The performance of the proposed transitions is cross-verified with a commercial software, and one design case is validated experimentally. PMID:28332585

Determination of volatile monophenols in beer using acetylation and headspace solid-phase microextraction in combination with gas chromatography and mass spectrometry.

PubMed

Sterckx, Femke L; Saison, Daan; Delvaux, Freddy R

2010-08-31

Monophenols are widely spread compounds contributing to the flavour of many foods and beverages. They are most likely present in beer, but so far, little is known about their influence on beer flavour. To quantify these monophenols in beer, we optimised a headspace solid-phase microextraction method coupled to gas chromatography-mass spectrometry. To improve their isolation from the beer matrix and their chromatographic properties, the monophenols were acetylated using acetic anhydride and KHCO(3) as derivatising agent and base catalyst, respectively. Derivatisation conditions were optimised with attention for the pH of the reaction medium. Additionally, different parameters affecting extraction efficiency were optimised, including fibre coating, extraction time and temperature and salt addition. Afterwards, we calibrated and validated the method successfully and applied it for the analysis of monophenols in beer samples. 2010 Elsevier B.V. All rights reserved.

Dwell time-based stabilisation of switched delay systems using free-weighting matrices

NASA Astrophysics Data System (ADS)

Koru, Ahmet Taha; Delibaşı, Akın; Özbay, Hitay

2018-01-01

In this paper, we present a quasi-convex optimisation method to minimise an upper bound of the dwell time for stability of switched delay systems. Piecewise Lyapunov-Krasovskii functionals are introduced and the upper bound for the derivative of Lyapunov functionals is estimated by free-weighting matrices method to investigate non-switching stability of each candidate subsystems. Then, a sufficient condition for the dwell time is derived to guarantee the asymptotic stability of the switched delay system. Once these conditions are represented by a set of linear matrix inequalities , dwell time optimisation problem can be formulated as a standard quasi-convex optimisation problem. Numerical examples are given to illustrate the improvements over previously obtained dwell time bounds. Using the results obtained in the stability case, we present a nonlinear minimisation algorithm to synthesise the dwell time minimiser controllers. The algorithm solves the problem with successive linearisation of nonlinear conditions.

3D Reconstruction of human bones based on dictionary learning.

PubMed

Zhang, Binkai; Wang, Xiang; Liang, Xiao; Zheng, Jinjin

2017-11-01

An effective method for reconstructing a 3D model of human bones from computed tomography (CT) image data based on dictionary learning is proposed. In this study, the dictionary comprises the vertices of triangular meshes, and the sparse coefficient matrix indicates the connectivity information. For better reconstruction performance, we proposed a balance coefficient between the approximation and regularisation terms and a method for optimisation. Moreover, we applied a local updating strategy and a mesh-optimisation method to update the dictionary and the sparse matrix, respectively. The two updating steps are iterated alternately until the objective function converges. Thus, a reconstructed mesh could be obtained with high accuracy and regularisation. The experimental results show that the proposed method has the potential to obtain high precision and high-quality triangular meshes for rapid prototyping, medical diagnosis, and tissue engineering. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Reservoir optimisation using El Niño information. Case study of Daule Peripa (Ecuador)

NASA Astrophysics Data System (ADS)

Gelati, Emiliano; Madsen, Henrik; Rosbjerg, Dan

2010-05-01

The optimisation of water resources systems requires the ability to produce runoff scenarios that are consistent with available climatic information. We approach stochastic runoff modelling with a Markov-modulated autoregressive model with exogenous input, which belongs to the class of Markov-switching models. The model assumes runoff parameterisation to be conditioned on a hidden climatic state following a Markov chain, whose state transition probabilities depend on climatic information. This approach allows stochastic modeling of non-stationary runoff, as runoff anomalies are described by a mixture of autoregressive models with exogenous input, each one corresponding to a climate state. We calibrate the model on the inflows of the Daule Peripa reservoir located in western Ecuador, where the occurrence of El Niño leads to anomalously heavy rainfall caused by positive sea surface temperature anomalies along the coast. El Niño - Southern Oscillation (ENSO) information is used to condition the runoff parameterisation. Inflow predictions are realistic, especially at the occurrence of El Niño events. The Daule Peripa reservoir serves a hydropower plant and a downstream water supply facility. Using historical ENSO records, synthetic monthly inflow scenarios are generated for the period 1950-2007. These scenarios are used as input to perform stochastic optimisation of the reservoir rule curves with a multi-objective Genetic Algorithm (MOGA). The optimised rule curves are assumed to be the reservoir base policy. ENSO standard indices are currently forecasted at monthly time scale with nine-month lead time. These forecasts are used to perform stochastic optimisation of reservoir releases at each monthly time step according to the following procedure: (i) nine-month inflow forecast scenarios are generated using ENSO forecasts; (ii) a MOGA is set up to optimise the upcoming nine monthly releases; (iii) the optimisation is carried out by simulating the releases on the inflow forecasts, and by applying the base policy on a subsequent synthetic inflow scenario in order to account for long-term costs; (iv) the optimised release for the first month is implemented; (v) the state of the system is updated and (i), (ii), (iii), and (iv) are iterated for the following time step. The results highlight the advantages of using a climate-driven stochastic model to produce inflow scenarios and forecasts for reservoir optimisation, showing potential improvements with respect to the current management. Dynamic programming was used to find the best possible release time series given the inflow observations, in order to benchmark any possible operational improvement.

Twist limits for late twisting double somersaults on trampoline.

PubMed

Yeadon, M R; Hiley, M J

2017-06-14

An angle-driven computer simulation model of aerial movement was used to determine the maximum amount of twist that could be produced in the second somersault of a double somersault on trampoline using asymmetrical movements of the arms and hips. Lower bounds were placed on the durations of arm and hip angle changes based on performances of a world trampoline champion whose inertia parameters were used in the simulations. The limiting movements were identified as the largest possible odd number of half twists for forward somersaulting takeoffs and even number of half twists for backward takeoffs. Simulations of these two limiting movements were found using simulated annealing optimisation to produce the required amounts of somersault, tilt and twist at landing after a flight time of 2.0s. Additional optimisations were then run to seek solutions with the arms less adducted during the twisting phase. It was found that 3½ twists could be produced in the second somersault of a forward piked double somersault with arms abducted 8° from full adduction during the twisting phase and that three twists could be produced in the second somersault of a backward straight double somersault with arms fully adducted to the body. These two movements are at the limits of performance for elite trampolinists. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis and optimisation of the convergence behaviour of the single channel digital tanlock loop

NASA Astrophysics Data System (ADS)

Al-Kharji Al-Ali, Omar; Anani, Nader; Al-Araji, Saleh; Al-Qutayri, Mahmoud

2013-09-01

The mathematical analysis of the convergence behaviour of the first-order single channel digital tanlock loop (SC-DTL) is presented. This article also describes a novel technique that allows controlling the convergence speed of the loop, i.e. the time taken by the phase-error to reach its steady-state value, by using a specialised controller unit. The controller is used to adjust the convergence speed so as to selectively optimise a given performance parameter of the loop. For instance, the controller may be used to speed up the convergence in order to increase the lock range and improve the acquisition speed. However, since increasing the lock range can degrade the noise immunity of the system, in a noisy environment the controller can slow down the convergence speed until locking is achieved. Once the system is in lock, the convergence speed can be increased to improve the acquisition speed. The performance of the SC-DTL system was assessed against similar arctan-based loops and the results demonstrate the success of the controller in optimising the performance of the SC-DTL loop. The results of the system testing using MATLAB/Simulink simulation are presented. A prototype of the proposed system was implemented using a field programmable gate array module and the practical results are in good agreement with those obtained by simulation.

An adaptive critic-based scheme for consensus control of nonlinear multi-agent systems

NASA Astrophysics Data System (ADS)

Heydari, Ali; Balakrishnan, S. N.

2014-12-01

The problem of decentralised consensus control of a network of heterogeneous nonlinear systems is formulated as an optimal tracking problem and a solution is proposed using an approximate dynamic programming based neurocontroller. The neurocontroller training comprises an initial offline training phase and an online re-optimisation phase to account for the fact that the reference signal subject to tracking is not fully known and available ahead of time, i.e., during the offline training phase. As long as the dynamics of the agents are controllable, and the communication graph has a directed spanning tree, this scheme guarantees the synchronisation/consensus even under switching communication topology and directed communication graph. Finally, an aerospace application is selected for the evaluation of the performance of the method. Simulation results demonstrate the potential of the scheme.

An FEM-based AI approach to model parameter identification for low vibration modes of wind turbine composite rotor blades

NASA Astrophysics Data System (ADS)

Navadeh, N.; Goroshko, I. O.; Zhuk, Y. A.; Fallah, A. S.

2017-11-01

An approach to construction of a beam-type simplified model of a horizontal axis wind turbine composite blade based on the finite element method is proposed. The model allows effective and accurate description of low vibration bending modes taking into account the effects of coupling between flapwise and lead-lag modes of vibration transpiring due to the non-uniform distribution of twist angle in the blade geometry along its length. The identification of model parameters is carried out on the basis of modal data obtained by more detailed finite element simulations and subsequent adoption of the 'DIRECT' optimisation algorithm. Stable identification results were obtained using absolute deviations in frequencies and in modal displacements in the objective function and additional a priori information (boundedness and monotony) on the solution properties.

The design of a Nai(Tl) crystal in a system optimised for high-throughput and emergency measurement of iodine 131 in the human thyroid

NASA Astrophysics Data System (ADS)

Vrba, Tomas; Fojtik, Pavel

2014-11-01

In the case of an accidental release of 131I, a system for large-scale monitoring of the population for the radionuclide intake is needed. A monitoring system is required to be capable of measuring adult as well as child subjects across a wide range of ages. Such system has been developed by the National Radiation Protection Institute in Prague (NRPI) and the Evinet company (member of the Nuvia Group). This paper describes the optimisation of the NaI(Tl) detector chosen for this system. The design of the crystal was based on Monte Carlo (MC) simulations, and supported by literature. These simulations examined three different crystal shapes and several dimensions. Based on the MC study, two prototype detectors, with crystal diameters 80 and 73 mm, were manufactured and compared with the crystals having dimensions ∅45×40 mm used for thyroid measurement at NRPI and with a standard NaI(Tl) probe (∅76.2×76.2 mm). The detector with a crystal of 80 mm diameter gave the best results and was chosen for further production.

Visual grading characteristics and ordinal regression analysis during optimisation of CT head examinations.

PubMed

Zarb, Francis; McEntee, Mark F; Rainford, Louise

2015-06-01

To evaluate visual grading characteristics (VGC) and ordinal regression analysis during head CT optimisation as a potential alternative to visual grading assessment (VGA), traditionally employed to score anatomical visualisation. Patient images (n = 66) were obtained using current and optimised imaging protocols from two CT suites: a 16-slice scanner at the national Maltese centre for trauma and a 64-slice scanner in a private centre. Local resident radiologists (n = 6) performed VGA followed by VGC and ordinal regression analysis. VGC alone indicated that optimised protocols had similar image quality as current protocols. Ordinal logistic regression analysis provided an in-depth evaluation, criterion by criterion allowing the selective implementation of the protocols. The local radiology review panel supported the implementation of optimised protocols for brain CT examinations (including trauma) in one centre, achieving radiation dose reductions ranging from 24 % to 36 %. In the second centre a 29 % reduction in radiation dose was achieved for follow-up cases. The combined use of VGC and ordinal logistic regression analysis led to clinical decisions being taken on the implementation of the optimised protocols. This improved method of image quality analysis provided the evidence to support imaging protocol optimisation, resulting in significant radiation dose savings. • There is need for scientifically based image quality evaluation during CT optimisation. • VGC and ordinal regression analysis in combination led to better informed clinical decisions. • VGC and ordinal regression analysis led to dose reductions without compromising diagnostic efficacy.

On simulated annealing phase transitions in phylogeny reconstruction.

PubMed

Strobl, Maximilian A R; Barker, Daniel

2016-08-01

Phylogeny reconstruction with global criteria is NP-complete or NP-hard, hence in general requires a heuristic search. We investigate the powerful, physically inspired, general-purpose heuristic simulated annealing, applied to phylogeny reconstruction. Simulated annealing mimics the physical process of annealing, where a liquid is gently cooled to form a crystal. During the search, periods of elevated specific heat occur, analogous to physical phase transitions. These simulated annealing phase transitions play a crucial role in the outcome of the search. Nevertheless, they have received comparably little attention, for phylogeny or other optimisation problems. We analyse simulated annealing phase transitions during searches for the optimal phylogenetic tree for 34 real-world multiple alignments. In the same way in which melting temperatures differ between materials, we observe distinct specific heat profiles for each input file. We propose this reflects differences in the search landscape and can serve as a measure for problem difficulty and for suitability of the algorithm's parameters. We discuss application in algorithmic optimisation and as a diagnostic to assess parameterisation before computationally costly, large phylogeny reconstructions are launched. Whilst the focus here lies on phylogeny reconstruction under maximum parsimony, it is plausible that our results are more widely applicable to optimisation procedures in science and industry. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Estimation of transversely isotropic material properties from magnetic resonance elastography using the optimised virtual fields method.

PubMed

Miller, Renee; Kolipaka, Arunark; Nash, Martyn P; Young, Alistair A

2018-03-12

Magnetic resonance elastography (MRE) has been used to estimate isotropic myocardial stiffness. However, anisotropic stiffness estimates may give insight into structural changes that occur in the myocardium as a result of pathologies such as diastolic heart failure. The virtual fields method (VFM) has been proposed for estimating material stiffness from image data. This study applied the optimised VFM to identify transversely isotropic material properties from both simulated harmonic displacements in a left ventricular (LV) model with a fibre field measured from histology as well as isotropic phantom MRE data. Two material model formulations were implemented, estimating either 3 or 5 material properties. The 3-parameter formulation writes the transversely isotropic constitutive relation in a way that dissociates the bulk modulus from other parameters. Accurate identification of transversely isotropic material properties in the LV model was shown to be dependent on the loading condition applied, amount of Gaussian noise in the signal, and frequency of excitation. Parameter sensitivity values showed that shear moduli are less sensitive to noise than the other parameters. This preliminary investigation showed the feasibility and limitations of using the VFM to identify transversely isotropic material properties from MRE images of a phantom as well as simulated harmonic displacements in an LV geometry. Copyright © 2018 John Wiley & Sons, Ltd.

BIANCA (Brain Intensity AbNormality Classification Algorithm): A new tool for automated segmentation of white matter hyperintensities.

PubMed

Griffanti, Ludovica; Zamboni, Giovanna; Khan, Aamira; Li, Linxin; Bonifacio, Guendalina; Sundaresan, Vaanathi; Schulz, Ursula G; Kuker, Wilhelm; Battaglini, Marco; Rothwell, Peter M; Jenkinson, Mark

2016-11-01

Reliable quantification of white matter hyperintensities of presumed vascular origin (WMHs) is increasingly needed, given the presence of these MRI findings in patients with several neurological and vascular disorders, as well as in elderly healthy subjects. We present BIANCA (Brain Intensity AbNormality Classification Algorithm), a fully automated, supervised method for WMH detection, based on the k-nearest neighbour (k-NN) algorithm. Relative to previous k-NN based segmentation methods, BIANCA offers different options for weighting the spatial information, local spatial intensity averaging, and different options for the choice of the number and location of the training points. BIANCA is multimodal and highly flexible so that the user can adapt the tool to their protocol and specific needs. We optimised and validated BIANCA on two datasets with different MRI protocols and patient populations (a "predominantly neurodegenerative" and a "predominantly vascular" cohort). BIANCA was first optimised on a subset of images for each dataset in terms of overlap and volumetric agreement with a manually segmented WMH mask. The correlation between the volumes extracted with BIANCA (using the optimised set of options), the volumes extracted from the manual masks and visual ratings showed that BIANCA is a valid alternative to manual segmentation. The optimised set of options was then applied to the whole cohorts and the resulting WMH volume estimates showed good correlations with visual ratings and with age. Finally, we performed a reproducibility test, to evaluate the robustness of BIANCA, and compared BIANCA performance against existing methods. Our findings suggest that BIANCA, which will be freely available as part of the FSL package, is a reliable method for automated WMH segmentation in large cross-sectional cohort studies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Determination of somatropin charged variants by capillary zone electrophoresis - optimisation, verification and implementation of the European pharmacopoeia method.

PubMed

Storms, S M; Feltus, A; Barker, A R; Joly, M-A; Girard, M

2009-03-01

Measurement of somatropin charged variants by isoelectric focusing was replaced with capillary zone electrophoresis in the January 2006 European Pharmacopoeia Supplement 5.3, based on results from an interlaboratory collaborative study. Due to incompatibilities and method-robustness issues encountered prior to verification, a number of method parameters required optimisation. As the use of a diode array detector at 195 nm or 200 nm led to a loss of resolution, a variable wavelength detector using a 200 nm filter was employed. Improved injection repeatability was obtained by increasing the injection time and pressure, and changing the sample diluent from water to running buffer. Finally, definition of capillary pre-treatment and rinse procedures resulted in more consistent separations over time. Method verification data are presented demonstrating linearity, specificity, repeatability, intermediate precision, limit of quantitation, sample stability, solution stability, and robustness. Based on these experiments, several modifications to the current method have been recommended and incorporated into the European Pharmacopoeia to help improve method performance across laboratories globally.

Better powder diffractometers. II—Optimal choice of U, V and W

NASA Astrophysics Data System (ADS)

Cussen, L. D.

2007-12-01

This article presents a technique for optimising constant wavelength (CW) neutron powder diffractometers (NPDs) using conventional nonlinear least squares methods. This is believed to be the first such design optimisation for a neutron spectrometer. The validity of this approach and discussion should extend beyond the Gaussian element approximation used and also to instruments using different radiation, such as X-rays. This approach could later be extended to include vertical and perhaps horizontal focusing monochromators and probably other types of instruments such as three axis spectrometers. It is hoped that this approach will help in comparisons of CW and time-of-flight (TOF) instruments. Recent work showed that many different beam element combinations can give identical resolution on CW NPDs and presented a procedure to find these combinations and also find an "optimum" choice of detector collimation. Those results enable the previous redundancy in the description of instrument performance to be removed and permit a least squares optimisation of design. New inputs are needed and are identified as the sample plane spacing ( dS) of interest in the measurement. The optimisation requires a "quality factor", QPD, chosen here to be minimising the worst Bragg peak separation ability over some measurement range ( dS) while maintaining intensity. Any other QPD desired could be substituted. It is argued that high resolution and high intensity powder diffractometers (HRPDs and HIPDs) should have similar designs adjusted by a single scaling factor. Simulated comparisons are described suggesting significant improvements in performance for CW HIPDs. Optimisation with unchanged wavelength suggests improvements by factors of about 2 for HRPDs and 25 for HIPDs. A recently quantified design trade-off between the maximum line intensity possible and the degree of variation of angular resolution over the scattering angle range leads to efficiency gains at short wavelengths. This in turn leads in practice to another trade-off between this efficiency gain and losses at short wavelength due to technical effects. The exact gains from varying wavelength depend on the details of the short wavelength technical losses. Simulations suggest that the total potential PD performance gains may be very significant-factors of about 3 for HRPDs and more than 90 for HIPDs.

Optimisation of novel method for the extraction of steviosides from Stevia rebaudiana leaves.

PubMed

Puri, Munish; Sharma, Deepika; Barrow, Colin J; Tiwary, A K

2012-06-01

Stevioside, a diterpene glycoside, is well known for its intense sweetness and is used as a non-caloric sweetener. Its potential widespread use requires an easy and effective extraction method. Enzymatic extraction of stevioside from Stevia rebaudiana leaves with cellulase, pectinase and hemicellulase, using various parameters, such as concentration of enzyme, incubation time and temperature, was optimised. Hemicellulase was observed to give the highest stevioside yield (369.23±0.11μg) in 1h in comparison to cellulase (359±0.30μg) and pectinases (333±0.55μg). Extraction from leaves under optimised conditions showed a remarkable increase in the yield (35 times) compared with a control experiment. The extraction conditions were further optimised using response surface methodology (RSM). A central composite design (CCD) was used for experimental design and analysis of the results to obtain optimal extraction conditions. Based on RSM analysis, temperature of 51-54°C, time of 36-45min and the cocktail of pectinase, cellulase and hemicellulase, set at 2% each, gave the best results. Under the optimised conditions, the experimental values were in close agreement with the prediction model and resulted in a three times yield enhancement of stevioside. The isolated stevioside was characterised through 1 H-NMR spectroscopy, by comparison with a stevioside standard. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed

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.

The effect of resistance level and stability demands on recruitment patterns and internal loading of spine in dynamic flexion and extension using a simple trunk model.

PubMed

Zeinali-Davarani, Shahrokh; Shirazi-Adl, Aboulfazl; Dariush, Behzad; Hemami, Hooshang; Parnianpour, Mohamad

2011-07-01

The effects of external resistance on the recruitment of trunk muscles in sagittal movements and the coactivation mechanism to maintain spinal stability were investigated using a simple computational model of iso-resistive spine sagittal movements. Neural excitation of muscles was attained based on inverse dynamics approach along with a stability-based optimisation. The trunk flexion and extension movements between 60° flexion and the upright posture against various resistance levels were simulated. Incorporation of the stability constraint in the optimisation algorithm required higher antagonistic activities for all resistance levels mostly close to the upright position. Extension movements showed higher coactivation with higher resistance, whereas flexion movements demonstrated lower coactivation indicating a greater stability demand in backward extension movements against higher resistance at the neighbourhood of the upright posture. Optimal extension profiles based on minimum jerk, work and power had distinct kinematics profiles which led to recruitment patterns with different timing and amplitude of activation.

SU-F-T-184: 3D Range-Modulator for Scanned Particle Therapy: Development, Monte Carlo Simulations and Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simeonov, Y; Penchev, P; Ringbaek, T Printz

2016-06-15

Purpose: Active raster scanning in particle therapy results in highly conformal dose distributions. Treatment time, however, is relatively high due to the large number of different iso-energy layers used. By using only one energy and the so called 3D range-modulator irradiation times of a few seconds only can be achieved, thus making delivery of homogeneous dose to moving targets (e.g. lung cancer) more reliable. Methods: A 3D range-modulator consisting of many pins with base area of 2.25 mm2 and different lengths was developed and manufactured with rapid prototyping technique. The form of the 3D range-modulator was optimised for a sphericalmore » target volume with 5 cm diameter placed at 25 cm in a water phantom. Monte Carlo simulations using the FLUKA package were carried out to evaluate the modulating effect of the 3D range-modulator and simulate the resulting dose distribution. The fine and complicated contour form of the 3D range-modulator was taken into account by a specially programmed user routine. Additionally FLUKA was extended with the capability of intensity modulated scanning. To verify the simulation results dose measurements were carried out at the Heidelberg Ion Therapy Center (HIT) with a 400.41 MeV 12C beam. Results: The high resolution measurements show that the 3D range-modulator is capable of producing homogeneous 3D conformal dose distributions, simultaneously reducing significantly irradiation time. Measured dose is in very good agreement with the previously conducted FLUKA simulations, where slight differences were traced back to minor manufacturing deviations from the perfect optimised form. Conclusion: Combined with the advantages of very short treatment time the 3D range-modulator could be an alternative to treat small to medium sized tumours (e.g. lung metastasis) with the same conformity as full raster-scanning treatment. Further simulations and measurements of more complex cases will be conducted to investigate the full potential of the 3D range-modulator.« less

Optimisation of logistics processes of energy grass collection

NASA Astrophysics Data System (ADS)

Bányai, Tamás.

2010-05-01

The collection of energy grass is a logistics-intensive process [1]. The optimal design and control of transportation and collection subprocesses is a critical point of the supply chain. To avoid irresponsible decisions by right of experience and intuition, the optimisation and analysis of collection processes based on mathematical models and methods is the scientific suggestible way. Within the frame of this work, the author focuses on the optimisation possibilities of the collection processes, especially from the point of view transportation and related warehousing operations. However the developed optimisation methods in the literature [2] take into account the harvesting processes, county-specific yields, transportation distances, erosion constraints, machinery specifications, and other key variables, but the possibility of more collection points and the multi-level collection were not taken into consideration. The possible areas of using energy grass is very wide (energetically use, biogas and bio alcohol production, paper and textile industry, industrial fibre material, foddering purposes, biological soil protection [3], etc.), so not only a single level but also a multi-level collection system with more collection and production facilities has to be taken into consideration. The input parameters of the optimisation problem are the followings: total amount of energy grass to be harvested in each region; specific facility costs of collection, warehousing and production units; specific costs of transportation resources; pre-scheduling of harvesting process; specific transportation and warehousing costs; pre-scheduling of processing of energy grass at each facility (exclusive warehousing). The model take into consideration the following assumptions: (1) cooperative relation among processing and production facilties, (2) capacity constraints are not ignored, (3) the cost function of transportation is non-linear, (4) the drivers conditions are ignored. The 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 Fund. References [1] P. R. Daniel: The Economics of Harvesting and Transporting Corn Stover for Conversion to Fuel Ethanol: A Case Study for Minnesota. University of Minnesota, Department of Applied Economics. 2006. http://ideas.repec.org/p/ags/umaesp/14213.html [2] T. G. Douglas, J. Brendan, D. Erin & V.-D. Becca: Energy and Chemicals from Native Grasses: Production, Transportation and Processing Technologies Considered in the Northern Great Plains. University of Minnesota, Department of Applied Economics. 2006. http://ideas.repec.org/p/ags/umaesp/13838.html [3] Homepage of energygrass. www.energiafu.hu

Evaluation of simulation alternatives for the brute-force ray-tracing approach used in backlight design

NASA Astrophysics Data System (ADS)

Desnijder, Karel; Hanselaer, Peter; Meuret, Youri

2016-04-01

A key requirement to obtain a uniform luminance for a side-lit LED backlight is the optimised spatial pattern of structures on the light guide that extract the light. The generation of such a scatter pattern is usually performed by applying an iterative approach. In each iteration, the luminance distribution of the backlight with a particular scatter pattern is analysed. This is typically performed with a brute-force ray-tracing algorithm, although this approach results in a time-consuming optimisation process. In this study, the Adding-Doubling method is explored as an alternative way for evaluating the luminance of a backlight. Due to the similarities between light propagating in a backlight with extraction structures and light scattering in a cloud of light scatterers, the Adding-Doubling method which is used to model the latter could also be used to model the light distribution in a backlight. The backlight problem is translated to a form upon which the Adding-Doubling method is directly applicable. The calculated luminance for a simple uniform extraction pattern with the Adding-Doubling method matches the luminance generated by a commercial raytracer very well. Although successful, no clear computational advantage over ray tracers is realised. However, the dynamics of light propagation in a light guide as used the Adding-Doubling method, also allow to enhance the efficiency of brute-force ray-tracing algorithms. The performance of this enhanced ray-tracing approach for the simulation of backlights is also evaluated against a typical brute-force ray-tracing approach.

Study on optimal design of 210kW traction IPMSM considering thermal demagnetization characteristics

NASA Astrophysics Data System (ADS)

Kim, Young Hyun; Lee, Seong Soo; Cheon, Byung Chul; Lee, Jung Ho

2018-04-01

This study analyses the permanent magnet (PM) used in the rotor of an interior permanent magnet synchronous motor (IPMSM) used for driving an electric railway vehicle (ERV) in the context of controllable shape, temperature, and external magnetic field. The positioning of the inserted magnets is a degree of freedom in the design of such machines. This paper describes a preliminary analysis using parametric finite-element method performed with the aim of achieving an effective design. Next, features of the experimental design, based on methods such as the central-composition method, Box-Behnken and Taguchi method, are explored to optimise the shape of the high power density. The results are used to produce an optimal design for IPMSMs, with design errors minimized using Maxwell 2D, a commercial program. Furthermore, the demagnetization process is analysed based on the magnetization and demagnetization theory for PM materials in computer simulation. The result of the analysis can be used to calculate the magnetization and demagnetization phenomenon according to the input B-H curve. This paper presents the conditions for demagnetization by the external magnetic field in the driving and stopped states, and proposes a simulation method that can analyse demagnetization phenomena according to each condition and design the IPMSM that maximizes efficiency and torque characteristics. Finally, operational characteristics are analysed in terms of the operation patterns of railway vehicles, and control conditions are deduced to achieve maximum efficiency in all sections. This was experimentally verified.

The development and optimisation of a primary care-based whole system complex intervention (CARE Plus) for patients with multimorbidity living in areas of high socioeconomic deprivation

PubMed Central

O'Brien, Rosaleen; Fitzpatrick, Bridie; Higgins, Maria; Guthrie, Bruce; Watt, Graham; Wyke, Sally

2016-01-01

Objectives To develop and optimise a primary care-based complex intervention (CARE Plus) to enhance the quality of life of patients with multimorbidity in the deprived areas. Methods Six co-design discussion groups involving 32 participants were held separately with multimorbid patients from the deprived areas, voluntary organisations, general practitioners and practice nurses working in the deprived areas. This was followed by piloting in two practices and further optimisation based on interviews with 11 general practitioners, 2 practice nurses and 6 participating multimorbid patients. Results Participants endorsed the need for longer consultations, relational continuity and a holistic approach. All felt that training and support of the health care staff was important. Most participants welcomed the idea of additional self-management support, though some practitioners were dubious about whether patients would use it. The pilot study led to changes including a revised care plan, the inclusion of mindfulness-based stress reduction techniques in the support of practitioners and patients, and the stream-lining of the written self-management support material for patients. Discussion We have co-designed and optimised an augmented primary care intervention involving a whole-system approach to enhance quality of life in multimorbid patients living in the deprived areas. CARE Plus will next be tested in a phase 2 cluster randomised controlled trial. PMID:27068113

A method for measuring particle number emissions from vehicles driving on the road.

PubMed

Shi, J P; Harrison, R M; Evans, D E; Alam, A; Barnes, C; Carter, G

2002-01-01

Earlier research has demonstrated that the conditions of dilution of engine exhaust gases profoundly influence the size distribution and total number of particles emitted. Since real world dilution conditions are variable and therefore difficult to simulate, this research has sought to develop and validate a method for measuring particle number emissions from vehicles driving past on a road. This has been achieved successfully using carbon dioxide as a tracer of exhaust gas dilution. By subsequent adjustment of data to a constant dilution factor, it is possible to compare emissions from different vehicles using different technologies and fuels based upon real world emission data. Whilst further optimisation of the technique, especially in terms of matching the instrument response times is desirable, the measurements offer useful insights into emissions from gasoline and diesel vehicles, and the substantial proportion of particles emitted in the 3-7 nanometre size range.

Radiation dose optimisation for conventional imaging in infants and newborns using automatic dose management software: an application of the new 2013/59 EURATOM directive.

PubMed

Alejo, L; Corredoira, E; Sánchez-Muñoz, F; Huerga, C; Aza, Z; Plaza-Núñez, R; Serrada, A; Bret-Zurita, M; Parrón, M; Prieto-Areyano, C; Garzón-Moll, G; Madero, R; Guibelalde, E

2018-04-09

Objective: The new 2013/59 EURATOM Directive (ED) demands dosimetric optimisation procedures without undue delay. The aim of this study was to optimise paediatric conventional radiology examinations applying the ED without compromising the clinical diagnosis. Automatic dose management software (ADMS) was used to analyse 2678 studies of children from birth to 5 years of age, obtaining local diagnostic reference levels (DRLs) in terms of entrance surface air kerma. Given local DRL for infants and chest examinations exceeded the European Commission (EC) DRL, an optimisation was performed decreasing the kVp and applying the automatic control exposure. To assess the image quality, an analysis of high-contrast resolution (HCSR), signal-to-noise ratio (SNR) and figure of merit (FOM) was performed, as well as a blind test based on the generalised estimating equations method. For newborns and chest examinations, the local DRL exceeded the EC DRL by 113%. After the optimisation, a reduction of 54% was obtained. No significant differences were found in the image quality blind test. A decrease in SNR (-37%) and HCSR (-68%), and an increase in FOM (42%), was observed. ADMS allows the fast calculation of local DRLs and the performance of optimisation procedures in babies without delay. However, physical and clinical analyses of image quality remain to be needed to ensure the diagnostic integrity after the optimisation process. Advances in knowledge: ADMS are useful to detect radiation protection problems and to perform optimisation procedures in paediatric conventional imaging without undue delay, as ED requires.

H∞ output tracking control of uncertain and disturbed nonlinear systems based on neural network model

NASA Astrophysics Data System (ADS)

Li, Chengcheng; Li, Yuefeng; Wang, Guanglin

2017-07-01

The work presented in this paper seeks to address the tracking problem for uncertain continuous nonlinear systems with external disturbances. The objective is to obtain a model that uses a reference-based output feedback tracking control law. The control scheme is based on neural networks and a linear difference inclusion (LDI) model, and a PDC structure and H∞ performance criterion are used to attenuate external disturbances. The stability of the whole closed-loop model is investigated using the well-known quadratic Lyapunov function. The key principles of the proposed approach are as follows: neural networks are first used to approximate nonlinearities, to enable a nonlinear system to then be represented as a linearised LDI model. An LMI (linear matrix inequality) formula is obtained for uncertain and disturbed linear systems. This formula enables a solution to be obtained through an interior point optimisation method for some nonlinear output tracking control problems. Finally, simulations and comparisons are provided on two practical examples to illustrate the validity and effectiveness of the proposed method.

An imperialist competitive algorithm for virtual machine placement in cloud computing

NASA Astrophysics Data System (ADS)

Jamali, Shahram; Malektaji, Sepideh; Analoui, Morteza

2017-05-01

Cloud computing, the recently emerged revolution in IT industry, is empowered by virtualisation technology. In this paradigm, the user's applications run over some virtual machines (VMs). The process of selecting proper physical machines to host these virtual machines is called virtual machine placement. It plays an important role on resource utilisation and power efficiency of cloud computing environment. In this paper, we propose an imperialist competitive-based algorithm for the virtual machine placement problem called ICA-VMPLC. The base optimisation algorithm is chosen to be ICA because of its ease in neighbourhood movement, good convergence rate and suitable terminology. The proposed algorithm investigates search space in a unique manner to efficiently obtain optimal placement solution that simultaneously minimises power consumption and total resource wastage. Its final solution performance is compared with several existing methods such as grouping genetic and ant colony-based algorithms as well as bin packing heuristic. The simulation results show that the proposed method is superior to other tested algorithms in terms of power consumption, resource wastage, CPU usage efficiency and memory usage efficiency.

Estimation of Power Consumption in the Circular Sawing of Stone Based on Tangential Force Distribution

NASA Astrophysics Data System (ADS)

Huang, Guoqin; Zhang, Meiqin; Huang, Hui; Guo, Hua; Xu, Xipeng

2018-04-01

Circular sawing is an important method for the processing of natural stone. The ability to predict sawing power is important in the optimisation, monitoring and control of the sawing process. In this paper, a predictive model (PFD) of sawing power, which is based on the tangential force distribution at the sawing contact zone, was proposed, experimentally validated and modified. With regard to the influence of sawing speed on tangential force distribution, the modified PFD (MPFD) performed with high predictive accuracy across a wide range of sawing parameters, including sawing speed. The mean maximum absolute error rate was within 6.78%, and the maximum absolute error rate was within 11.7%. The practicability of predicting sawing power by the MPFD with few initial experimental samples was proved in case studies. On the premise of high sample measurement accuracy, only two samples are required for a fixed sawing speed. The feasibility of applying the MPFD to optimise sawing parameters while lowering the energy consumption of the sawing system was validated. The case study shows that energy use was reduced 28% by optimising the sawing parameters. The MPFD model can be used to predict sawing power, optimise sawing parameters and control energy.

Optimisation of Critical Infrastructure Protection: The SiVe Project on Airport Security

NASA Astrophysics Data System (ADS)

Breiing, Marcus; Cole, Mara; D'Avanzo, John; Geiger, Gebhard; Goldner, Sascha; Kuhlmann, Andreas; Lorenz, Claudia; Papproth, Alf; Petzel, Erhard; Schwetje, Oliver

This paper outlines the scientific goals, ongoing work and first results of the SiVe research project on critical infrastructure security. The methodology is generic while pilot studies are chosen from airport security. The outline proceeds in three major steps, (1) building a threat scenario, (2) development of simulation models as scenario refinements, and (3) assessment of alternatives. Advanced techniques of systems analysis and simulation are employed to model relevant airport structures and processes as well as offences. Computer experiments are carried out to compare and optimise alternative solutions. The optimality analyses draw on approaches to quantitative risk assessment recently developed in the operational sciences. To exploit the advantages of the various techniques, an integrated simulation workbench is build up in the project.

Optimisation and validation of a rapid and efficient microemulsion liquid chromatographic (MELC) method for the determination of paracetamol (acetaminophen) content in a suppository formulation.

PubMed

McEvoy, Eamon; Donegan, Sheila; Power, Joe; Altria, Kevin

2007-05-09

A rapid and efficient oil-in-water microemulsion liquid chromatographic method has been optimised and validated for the analysis of paracetamol in a suppository formulation. Excellent linearity, accuracy, precision and assay results were obtained. Lengthy sample pre-treatment/extraction procedures were eliminated due to the solubilising power of the microemulsion and rapid analysis times were achieved. The method was optimised to achieve rapid analysis time and relatively high peak efficiencies. A standard microemulsion composition of 33 g SDS, 66 g butan-1-ol, 8 g n-octane in 1l of 0.05% TFA modified with acetonitrile has been shown to be suitable for the rapid analysis of paracetamol in highly hydrophobic preparations under isocratic conditions. Validated assay results and overall analysis time of the optimised method was compared to British Pharmacopoeia reference methods. Sample preparation and analysis times for the MELC analysis of paracetamol in a suppository were extremely rapid compared to the reference method and similar assay results were achieved. A gradient MELC method using the same microemulsion has been optimised for the resolution of paracetamol and five of its related substances in approximately 7 min.

Measurements and TCAD simulation of novel ATLAS planar pixel detector structures for the HL-LHC upgrade

NASA Astrophysics Data System (ADS)

Nellist, C.; Dinu, N.; Gkougkousis, E.; Lounis, A.

2015-06-01

The LHC accelerator complex will be upgraded between 2020-2022, to the High-Luminosity-LHC, to considerably increase statistics for the various physics analyses. To operate under these challenging new conditions, and maintain excellent performance in track reconstruction and vertex location, the ATLAS pixel detector must be substantially upgraded and a full replacement is expected. Processing techniques for novel pixel designs are optimised through characterisation of test structures in a clean room and also through simulations with Technology Computer Aided Design (TCAD). A method to study non-perpendicular tracks through a pixel device is discussed. Comparison of TCAD simulations with Secondary Ion Mass Spectrometry (SIMS) measurements to investigate the doping profile of structures and validate the simulation process is also presented.

A chaotic model for advertising diffusion problem with competition

NASA Astrophysics Data System (ADS)

Ip, W. H.; Yung, K. L.; Wang, Dingwei

2012-08-01

In this article, the author extends Dawid and Feichtinger's chaotic advertising diffusion model into the duopoly case. A computer simulation system is used to test this enhanced model. Based on the analysis of simulation results, it is found that the best advertising strategy in duopoly is to increase the advertising investment to reach the best Win-Win situation where the oscillation of market portion will not occur. In order to effectively arrive at the best situation, we define a synthetic index and two thresholds. An estimation method for the parameters of the index and thresholds is proposed in this research. We can reach the Win-Win situation by simply selecting the control parameters to make the synthetic index close to the threshold of min-oscillation state. The numerical example and computational results indicated that the proposed chaotic model is useful to describe and analyse advertising diffusion process in duopoly, it is an efficient tool for the selection and optimisation of advertising strategy.

A Method for Decentralised Optimisation in Networks

NASA Astrophysics Data System (ADS)

Saramäki, Jari

2005-06-01

We outline a method for distributed Monte Carlo optimisation of computational problems in networks of agents, such as peer-to-peer networks of computers. The optimisation and messaging procedures are inspired by gossip protocols and epidemic data dissemination, and are decentralised, i.e. no central overseer is required. In the outlined method, each agent follows simple local rules and seeks for better solutions to the optimisation problem by Monte Carlo trials, as well as by querying other agents in its local neighbourhood. With proper network topology, good solutions spread rapidly through the network for further improvement. Furthermore, the system retains its functionality even in realistic settings where agents are randomly switched on and off.

Advanced data management for optimising the operation of a full-scale WWTP.

PubMed

Beltrán, Sergio; Maiza, Mikel; de la Sota, Alejandro; Villanueva, José María; Ayesa, Eduardo

2012-01-01

The lack of appropriate data management tools is presently a limiting factor for a broader implementation and a more efficient use of sensors and analysers, monitoring systems and process controllers in wastewater treatment plants (WWTPs). This paper presents a technical solution for advanced data management of a full-scale WWTP. The solution is based on an efficient and intelligent use of the plant data by a standard centralisation of the heterogeneous data acquired from different sources, effective data processing to extract adequate information, and a straightforward connection to other emerging tools focused on the operational optimisation of the plant such as advanced monitoring and control or dynamic simulators. A pilot study of the advanced data manager tool was designed and implemented in the Galindo-Bilbao WWTP. The results of the pilot study showed its potential for agile and intelligent plant data management by generating new enriched information combining data from different plant sources, facilitating the connection of operational support systems, and developing automatic plots and trends of simulated results and actual data for plant performance and diagnosis.

Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation

PubMed Central

2018-01-01

Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site. PMID:29370230

Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation.

PubMed

Illias, Hazlee Azil; Zhao Liang, Wee

2018-01-01

Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site.

Influence of the Size of Cohorts in Adaptive Design for Nonlinear Mixed Effects Models: An Evaluation by Simulation for a Pharmacokinetic and Pharmacodynamic Model for a Biomarker in Oncology.

PubMed

Lestini, Giulia; Dumont, Cyrielle; Mentré, France

2015-10-01

In this study we aimed to evaluate adaptive designs (ADs) by clinical trial simulation for a pharmacokinetic-pharmacodynamic model in oncology and to compare them with one-stage designs, i.e., when no adaptation is performed, using wrong prior parameters. We evaluated two one-stage designs, ξ0 and ξ*, optimised for prior and true population parameters, Ψ0 and Ψ*, and several ADs (two-, three- and five-stage). All designs had 50 patients. For ADs, the first cohort design was ξ0. The next cohort design was optimised using prior information updated from the previous cohort. Optimal design was based on the determinant of the Fisher information matrix using PFIM. Design evaluation was performed by clinical trial simulations using data simulated from Ψ*. Estimation results of two-stage ADs and ξ * were close and much better than those obtained with ξ 0. The balanced two-stage AD performed better than two-stage ADs with different cohort sizes. Three- and five-stage ADs were better than two-stage with small first cohort, but not better than the balanced two-stage design. Two-stage ADs are useful when prior parameters are unreliable. In case of small first cohort, more adaptations are needed but these designs are complex to implement.

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

DOE PAGES

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek; ...

2017-04-24

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

Metaheuristic simulation optimisation for the stochastic multi-retailer supply chain

NASA Astrophysics Data System (ADS)

Omar, Marina; Mustaffa, Noorfa Haszlinna H.; Othman, Siti Norsyahida

2013-04-01

Supply Chain Management (SCM) is an important activity in all producing facilities and in many organizations to enable vendors, manufacturers and suppliers to interact gainfully and plan optimally their flow of goods and services. A simulation optimization approach has been widely used in research nowadays on finding the best solution for decision-making process in Supply Chain Management (SCM) that generally faced a complexity with large sources of uncertainty and various decision factors. Metahueristic method is the most popular simulation optimization approach. However, very few researches have applied this approach in optimizing the simulation model for supply chains. Thus, this paper interested in evaluating the performance of metahueristic method for stochastic supply chains in determining the best flexible inventory replenishment parameters that minimize the total operating cost. The simulation optimization model is proposed based on the Bees algorithm (BA) which has been widely applied in engineering application such as training neural networks for pattern recognition. BA is a new member of meta-heuristics. BA tries to model natural behavior of honey bees in food foraging. Honey bees use several mechanisms like waggle dance to optimally locate food sources and to search new ones. This makes them a good candidate for developing new algorithms for solving optimization problems. This model considers an outbound centralised distribution system consisting of one supplier and 3 identical retailers and is assumed to be independent and identically distributed with unlimited supply capacity at supplier.

Optimisation of active suspension control inputs for improved performance of active safety systems

NASA Astrophysics Data System (ADS)

Čorić, Mirko; Deur, Joško; Xu, Li; Tseng, H. Eric; Hrovat, Davor

2018-01-01

A collocation-type control variable optimisation method is used to investigate the extent to which the fully active suspension (FAS) can be applied to improve the vehicle electronic stability control (ESC) performance and reduce the braking distance. First, the optimisation approach is applied to the scenario of vehicle stabilisation during the sine-with-dwell manoeuvre. The results are used to provide insights into different FAS control mechanisms for vehicle performance improvements related to responsiveness and yaw rate error reduction indices. The FAS control performance is compared to performances of the standard ESC system, optimal active brake system and combined FAS and ESC configuration. Second, the optimisation approach is employed to the task of FAS-based braking distance reduction for straight-line vehicle motion. Here, the scenarios of uniform and longitudinally or laterally non-uniform tyre-road friction coefficient are considered. The influences of limited anti-lock braking system (ABS) actuator bandwidth and limit-cycle ABS behaviour are also analysed. The optimisation results indicate that the FAS can provide competitive stabilisation performance and improved agility when compared to the ESC system, and that it can reduce the braking distance by up to 5% for distinctively non-uniform friction conditions.

Methods of increasing the performance of radionuclide generators used in nuclear medicine: daughter nuclide build-up optimisation, elution-purification-concentration integration, and effective control of radionuclidic purity.

PubMed

Le, Van So; Do, Zoe Phuc-Hien; Le, Minh Khoi; Le, Vicki; Le, Natalie Nha-Truc

2014-06-10

Methods of increasing the performance of radionuclide generators used in nuclear medicine radiotherapy and SPECT/PET imaging were developed and detailed for 99Mo/99mTc and 68Ge/68Ga radionuclide generators as the cases. Optimisation methods of the daughter nuclide build-up versus stand-by time and/or specific activity using mean progress functions were developed for increasing the performance of radionuclide generators. As a result of this optimisation, the separation of the daughter nuclide from its parent one should be performed at a defined optimal time to avoid the deterioration in specific activity of the daughter nuclide and wasting stand-by time of the generator, while the daughter nuclide yield is maintained to a reasonably high extent. A new characteristic parameter of the formation-decay kinetics of parent/daughter nuclide system was found and effectively used in the practice of the generator production and utilisation. A method of "early elution schedule" was also developed for increasing the daughter nuclide production yield and specific radioactivity, thus saving the cost of the generator and improving the quality of the daughter radionuclide solution. These newly developed optimisation methods in combination with an integrated elution-purification-concentration system of radionuclide generators recently developed is the most suitable way to operate the generator effectively on the basis of economic use and improvement of purposely suitable quality and specific activity of the produced daughter radionuclides. All these features benefit the economic use of the generator, the improved quality of labelling/scan, and the lowered cost of nuclear medicine procedure. Besides, a new method of quality control protocol set-up for post-delivery test of radionuclidic purity has been developed based on the relationship between gamma ray spectrometric detection limit, required limit of impure radionuclide activity and its measurement certainty with respect to optimising decay/measurement time and product sample activity used for QC quality control. The optimisation ensures a certainty of measurement of the specific impure radionuclide and avoids wasting the useful amount of valuable purified/concentrated daughter nuclide product. This process is important for the spectrometric measurement of very low activity of impure radionuclide contamination in the radioisotope products of much higher activity used in medical imaging and targeted radiotherapy.

Shape optimisation of an underwater Bernoulli gripper

NASA Astrophysics Data System (ADS)

Flint, Tim; Sellier, Mathieu

2015-11-01

In this work, we are interested in maximising the suction produced by an underwater Bernoulli gripper. Bernoulli grippers work by exploiting low pressure regions caused by the acceleration of a working fluid through a narrow channel, between the gripper and a surface, to provide a suction force. This mechanism allows for non-contact adhesion to various surfaces and may be used to hold a robot to the hull of a ship while it inspects welds for example. A Bernoulli type pressure analysis was used to model the system with a Darcy friction factor approximation to include the effects of frictional losses. The analysis involved a constrained optimisation in order to avoid cavitation within the mechanism which would result in decreased performance and damage to surfaces. A sensitivity based method and gradient descent approach was used to find the optimum shape of a discretised surface. The model's accuracy has been quantified against finite volume computational fluid dynamics simulation (ANSYS CFX) using the k- ω SST turbulence model. Preliminary results indicate significant improvement in suction force when compared to a simple geometry by retaining a pressure just above that at which cavitation would occur over as much surface area as possible. Doctoral candidate in the Mechanical Engineering Department of the University of Canterbury, New Zealand.

High-fidelity meshes from tissue samples for diffusion MRI simulations.

PubMed

Panagiotaki, Eleftheria; Hall, Matt G; Zhang, Hui; Siow, Bernard; Lythgoe, Mark F; Alexander, Daniel C

2010-01-01

This paper presents a method for constructing detailed geometric models of tissue microstructure for synthesizing realistic diffusion MRI data. We construct three-dimensional mesh models from confocal microscopy image stacks using the marching cubes algorithm. Random-walk simulations within the resulting meshes provide synthetic diffusion MRI measurements. Experiments optimise simulation parameters and complexity of the meshes to achieve accuracy and reproducibility while minimizing computation time. Finally we assess the quality of the synthesized data from the mesh models by comparison with scanner data as well as synthetic data from simple geometric models and simplified meshes that vary only in two dimensions. The results support the extra complexity of the three-dimensional mesh compared to simpler models although sensitivity to the mesh resolution is quite robust.

A rapid, automated approach to optimisation of multiple reaction monitoring conditions for quantitative bioanalytical mass spectrometry.

PubMed

Higton, D M

2001-01-01

An improvement to the procedure for the rapid optimisation of mass spectrometry (PROMS), for the development of multiple reaction methods (MRM) for quantitative bioanalytical liquid chromatography/tandem mass spectrometry (LC/MS/MS), is presented. PROMS is an automated protocol that uses flow-injection analysis (FIA) and AppleScripts to create methods and acquire the data for optimisation. The protocol determines the optimum orifice potential, the MRM conditions for each compound, and finally creates the MRM methods needed for sample analysis. The sensitivities of the MRM methods created by PROMS approach those created manually. MRM method development using PROMS currently takes less than three minutes per compound compared to at least fifteen minutes manually. To further enhance throughput, approaches to MRM optimisation using one injection per compound, two injections per pool of five compounds and one injection per pool of five compounds have been investigated. No significant difference in the optimised instrumental parameters for MRM methods were found between the original PROMS approach and these new methods, which are up to ten times faster. The time taken for an AppleScript to determine the optimum conditions and build the MRM methods is the same with all approaches. Copyright 2001 John Wiley & Sons, Ltd.

Catalytic CVD synthesis of boron nitride and carbon nanomaterials - synergies between experiment and theory.

PubMed

McLean, Ben; Eveleens, Clothilde A; Mitchell, Izaac; Webber, Grant B; Page, Alister J

2017-10-11

Low-dimensional carbon and boron nitride nanomaterials - hexagonal boron nitride, graphene, boron nitride nanotubes and carbon nanotubes - remain at the forefront of advanced materials research. Catalytic chemical vapour deposition has become an invaluable technique for reliably and cost-effectively synthesising these materials. In this review, we will emphasise how a synergy between experimental and theoretical methods has enhanced the understanding and optimisation of this synthetic technique. This review examines recent advances in the application of CVD to synthesising boron nitride and carbon nanomaterials and highlights where, in many cases, molecular simulations and quantum chemistry have provided key insights complementary to experimental investigation. This synergy is particularly prominent in the field of carbon nanotube and graphene CVD synthesis, and we propose here it will be the key to future advances in optimisation of CVD synthesis of boron nitride nanomaterials, boron nitride - carbon composite materials, and other nanomaterials generally.

Suppressing unsteady flow in arterio-venous fistulae

NASA Astrophysics Data System (ADS)

Grechy, L.; Iori, F.; Corbett, R. W.; Shurey, S.; Gedroyc, W.; Duncan, N.; Caro, C. G.; Vincent, P. E.

2017-10-01

Arterio-Venous Fistulae (AVF) are regarded as the "gold standard" method of vascular access for patients with end-stage renal disease who require haemodialysis. However, a large proportion of AVF do not mature, and hence fail, as a result of various pathologies such as Intimal Hyperplasia (IH). Unphysiological flow patterns, including high-frequency flow unsteadiness, associated with the unnatural and often complex geometries of AVF are believed to be implicated in the development of IH. In the present study, we employ a Mesh Adaptive Direct Search optimisation framework, computational fluid dynamics simulations, and a new cost function to design a novel non-planar AVF configuration that can suppress high-frequency unsteady flow. A prototype device for holding an AVF in the optimal configuration is then fabricated, and proof-of-concept is demonstrated in a porcine model. Results constitute the first use of numerical optimisation to design a device for suppressing potentially pathological high-frequency flow unsteadiness in AVF.

Thermal Performance Analysis of Solar Collectors Installed for Combisystem in the Apartment Building

NASA Astrophysics Data System (ADS)

Žandeckis, A.; Timma, L.; Blumberga, D.; Rochas, C.; Rošā, M.

2012-01-01

The paper focuses on the application of wood pellet and solar combisystem for space heating and hot water preparation at apartment buildings under the climate of Northern Europe. A pilot project has been implemented in the city of Sigulda (N 57° 09.410 E 024° 52.194), Latvia. The system was designed and optimised using TRNSYS - a dynamic simulation tool. The pilot project was continuously monitored. To the analysis the heat transfer fluid flow rate and the influence of the inlet temperature on the performance of solar collectors were subjected. The thermal performance of a solar collector loop was studied using a direct method. A multiple regression analysis was carried out using STATGRAPHICS Centurion 16.1.15 with the aim to identify the operational and weather parameters of the system which cause the strongest influence on the collector's performance. The parameters to be used for the system's optimisation have been evaluated.

Benchmarking nitrogen removal suspended-carrier biofilm systems using dynamic simulation.

PubMed

Vanhooren, H; Yuan, Z; Vanrolleghem, P A

2002-01-01

We are witnessing an enormous growth in biological nitrogen removal from wastewater. It presents specific challenges beyond traditional COD (carbon) removal. A possibility for optimised process design is the use of biomass-supporting media. In this paper, attached growth processes (AGP) are evaluated using dynamic simulations. The advantages of these systems that were qualitatively described elsewhere, are validated quantitatively based on a simulation benchmark for activated sludge treatment systems. This simulation benchmark is extended with a biofilm model that allows for fast and accurate simulation of the conversion of different substrates in a biofilm. The economic feasibility of this system is evaluated using the data generated with the benchmark simulations. Capital savings due to volume reduction and reduced sludge production are weighed out against increased aeration costs. In this evaluation, effluent quality is integrated as well.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rozhdestvensky, Yu V

The possibility is studied for obtaining intense cold atomic beams by using the Renyi entropy to optimise the laser cooling process. It is shown in the case of a Gaussian velocity distribution of atoms, the Renyi entropy coincides with the density of particles in the phase space. The optimisation procedure for cooling atoms by resonance optical radiation is described, which is based on the thermodynamic law of increasing the Renyi entropy in time. Our method is compared with the known methods for increasing the laser cooling efficiency such as the tuning of a laser frequency in time and a changemore » of the atomic transition frequency in an inhomogeneous transverse field of a magnetic solenoid. (laser cooling)« less

Molecular simulation of the thermophysical properties and phase behaviour of impure CO2 relevant to CCS.

PubMed

Cresswell, Alexander J; Wheatley, Richard J; Wilkinson, Richard D; Graham, Richard S

2016-10-20

Impurities from the CCS chain can greatly influence the physical properties of CO 2 . This has important design, safety and cost implications for the compression, transport and storage of CO 2 . There is an urgent need to understand and predict the properties of impure CO 2 to assist with CCS implementation. However, CCS presents demanding modelling requirements. A suitable model must both accurately and robustly predict CO 2 phase behaviour over a wide range of temperatures and pressures, and maintain that predictive power for CO 2 mixtures with numerous, mutually interacting chemical species. A promising technique to address this task is molecular simulation. It offers a molecular approach, with foundations in firmly established physical principles, along with the potential to predict the wide range of physical properties required for CCS. The quality of predictions from molecular simulation depends on accurate force-fields to describe the interactions between CO 2 and other molecules. Unfortunately, there is currently no universally applicable method to obtain force-fields suitable for molecular simulation. In this paper we present two methods of obtaining force-fields: the first being semi-empirical and the second using ab initio quantum-chemical calculations. In the first approach we optimise the impurity force-field against measurements of the phase and pressure-volume behaviour of CO 2 binary mixtures with N 2 , O 2 , Ar and H 2 . A gradient-free optimiser allows us to use the simulation itself as the underlying model. This leads to accurate and robust predictions under conditions relevant to CCS. In the second approach we use quantum-chemical calculations to produce ab initio evaluations of the interactions between CO 2 and relevant impurities, taking N 2 as an exemplar. We use a modest number of these calculations to train a machine-learning algorithm, known as a Gaussian process, to describe these data. The resulting model is then able to accurately predict a much broader set of ab initio force-field calculations at comparatively low numerical cost. Although our method is not yet ready to be implemented in a molecular simulation, we outline the necessary steps here. Such simulations have the potential to deliver first-principles simulation of the thermodynamic properties of impure CO 2 , without fitting to experimental data.

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

NASA Astrophysics Data System (ADS)

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.

Improving radiation hardness in space-based Charge-Coupled Devices through the narrowing of the charge transfer channel

NASA Astrophysics Data System (ADS)

Hall, D. J.; Skottfelt, J.; Soman, M. R.; Bush, N.; Holland, A.

2017-12-01

Charge-Coupled Devices (CCDs) have been the detector of choice for imaging and spectroscopy in space missions for several decades, such as those being used for the Euclid VIS instrument and baselined for the SMILE SXI. Despite the many positive properties of CCDs, such as the high quantum efficiency and low noise, when used in a space environment the detectors suffer damage from the often-harsh radiation environment. High energy particles can create defects in the silicon lattice which act to trap the signal electrons being transferred through the device, reducing the signal measured and effectively increasing the noise. We can reduce the impact of radiation on the devices through four key methods: increased radiation shielding, device design considerations, optimisation of operating conditions, and image correction. Here, we concentrate on device design operations, investigating the impact of narrowing the charge-transfer channel in the device with the aim of minimising the impact of traps during readout. Previous studies for the Euclid VIS instrument considered two devices, the e2v CCD204 and CCD273, the serial register of the former having a 50 μm channel and the latter having a 20 μm channel. The reduction in channel width was previously modelled to give an approximate 1.6× reduction in charge storage volume, verified experimentally to have a reduction in charge transfer inefficiency of 1.7×. The methods used to simulate the reduction approximated the charge cloud to a sharp-edged volume within which the probability of capture by traps was 100%. For high signals and slow readout speeds, this is a reasonable approximation. However, for low signals and higher readout speeds, the approximation falls short. Here we discuss a new method of simulating and calculating charge storage variations with device design changes, considering the absolute probability of capture across the pixel, bringing validity to all signal sizes and readout speeds. Using this method, we can optimise the device design to suffer minimum impact from radiation damage effects, here using detector development for the SMILE mission to demonstrate the process.

Virtual tryout planning in automotive industry based on simulation metamodels

NASA Astrophysics Data System (ADS)

Harsch, D.; Heingärtner, J.; Hortig, D.; Hora, P.

2016-11-01

Deep drawn sheet metal parts are increasingly designed to the feasibility limit, thus achieving a robust manufacturing is often challenging. The fluctuation of process and material properties often lead to robustness problems. Therefore, numerical simulations are used to detect the critical regions. To enhance the agreement with the real process conditions, the material data are acquired through a variety of experiments. Furthermore, the force distribution is taken into account. The simulation metamodel contains the virtual knowledge of a particular forming process, which is determined based on a series of finite element simulations with variable input parameters. Based on the metamodels, virtual process windows can be displayed for different configurations. This helps to improve the operating point as well as to adjust process settings in case the process becomes unstable. Furthermore, the time of tool tryout can be shortened due to transfer of the virtual knowledge contained in the metamodels on the optimisation of the drawbeads. This allows the tool manufacturer to focus on the essential, to save time and to recognize complex relationships.

Tanlock loop noise reduction using an optimised phase detector

NASA Astrophysics Data System (ADS)

Al-kharji Al-Ali, Omar; Anani, Nader; Al-Qutayri, Mahmoud; Al-Araji, Saleh

2013-06-01

This article proposes a time-delay digital tanlock loop (TDTL), which uses a new phase detector (PD) design that is optimised for noise reduction making it amenable for applications that require wide lock range without sacrificing the level of noise immunity. The proposed system uses an improved phase detector design which uses two phase detectors; one PD is used to optimise the noise immunity whilst the other is used to control the acquisition time of the TDTL system. Using the modified phase detector it is possible to reduce the second- and higher-order harmonics by at least 50% compared with the conventional TDTL system. The proposed system was simulated and tested using MATLAB/Simulink using frequency step inputs and inputs corrupted with varying levels of harmonic distortion. A hardware prototype of the system was implemented using a field programmable gate array (FPGA). The practical and simulation results indicate considerable improvement in the noise performance of the proposed system over the conventional TDTL architecture.

Basis for the development of sustainable optimisation indicators for activated sludge wastewater treatment plants in the Republic of Ireland.

PubMed

Gordon, G T; McCann, B P

2015-01-01

This paper describes the basis of a stakeholder-based sustainable optimisation indicator (SOI) system to be developed for small-to-medium sized activated sludge (AS) wastewater treatment plants (WwTPs) in the Republic of Ireland (ROI). Key technical publications relating to best practice plant operation, performance audits and optimisation, and indicator and benchmarking systems for wastewater services are identified. Optimisation studies were developed at a number of Irish AS WwTPs and key findings are presented. A national AS WwTP manager/operator survey was carried out to verify the applied operational findings and identify the key operator stakeholder requirements for this proposed SOI system. It was found that most plants require more consistent operational data-based decision-making, monitoring and communication structures to facilitate optimised, sustainable and continuous performance improvement. The applied optimisation and stakeholder consultation phases form the basis of the proposed stakeholder-based SOI system. This system will allow for continuous monitoring and rating of plant performance, facilitate optimised operation and encourage the prioritisation of performance improvement through tracking key operational metrics. Plant optimisation has become a major focus due to the transfer of all ROI water services to a national water utility from individual local authorities and the implementation of the EU Water Framework Directive.

Model-based performance and energy analyses of reverse osmosis to reuse wastewater in a PVC production site.

PubMed

Hu, Kang; Fiedler, Thorsten; Blanco, Laura; Geissen, Sven-Uwe; Zander, Simon; Prieto, David; Blanco, Angeles; Negro, Carlos; Swinnen, Nathalie

2017-11-10

A pilot-scale reverse osmosis (RO) followed behind a membrane bioreactor (MBR) was developed for the desalination to reuse wastewater in a PVC production site. The solution-diffusion-film model (SDFM) based on the solution-diffusion model (SDM) and the film theory was proposed to describe rejections of electrolyte mixtures in the MBR effluent which consists of dominant ions (Na + and Cl - ) and several trace ions (Ca 2+ , Mg 2+ , K + and SO 4 2- ). The universal global optimisation method was used to estimate the ion permeability coefficients (B) and mass transfer coefficients (K) in SDFM. Then, the membrane performance was evaluated based on the estimated parameters which demonstrated that the theoretical simulations were in line with the experimental results for the dominant ions. Moreover, an energy analysis model with the consideration of limitation imposed by the thermodynamic restriction was proposed to analyse the specific energy consumption of the pilot-scale RO system in various scenarios.

A radiobiology-based inverse treatment planning method for optimisation of permanent l-125 prostate implants in focal brachytherapy.

PubMed

Haworth, Annette; Mears, Christopher; Betts, John M; Reynolds, Hayley M; Tack, Guido; Leo, Kevin; Williams, Scott; Ebert, Martin A

2016-01-07

Treatment plans for ten patients, initially treated with a conventional approach to low dose-rate brachytherapy (LDR, 145 Gy to entire prostate), were compared with plans for the same patients created with an inverse-optimisation planning process utilising a biologically-based objective. The 'biological optimisation' considered a non-uniform distribution of tumour cell density through the prostate based on known and expected locations of the tumour. Using dose planning-objectives derived from our previous biological-model validation study, the volume of the urethra receiving 125% of the conventional prescription (145 Gy) was reduced from a median value of 64% to less than 8% whilst maintaining high values of TCP. On average, the number of planned seeds was reduced from 85 to less than 75. The robustness of plans to random seed displacements needs to be carefully considered when using contemporary seed placement techniques. We conclude that an inverse planning approach to LDR treatments, based on a biological objective, has the potential to maintain high rates of tumour control whilst minimising dose to healthy tissue. In future, the radiobiological model will be informed using multi-parametric MRI to provide a personalised medicine approach.

Optimising operational amplifiers by evolutionary algorithms and gm/Id method

NASA Astrophysics Data System (ADS)

Tlelo-Cuautle, E.; Sanabria-Borbon, A. C.

2016-10-01

The evolutionary algorithm called non-dominated sorting genetic algorithm (NSGA-II) is applied herein in the optimisation of operational transconductance amplifiers. NSGA-II is accelerated by applying the gm/Id method to estimate reduced search spaces associated to widths (W) and lengths (L) of the metal-oxide-semiconductor field-effect-transistor (MOSFETs), and to guarantee their appropriate bias levels conditions. In addition, we introduce an integer encoding for the W/L sizes of the MOSFETs to avoid a post-processing step for rounding-off their values to be multiples of the integrated circuit fabrication technology. Finally, from the feasible solutions generated by NSGA-II, we introduce a second optimisation stage to guarantee that the final feasible W/L sizes solutions support process, voltage and temperature (PVT) variations. The optimisation results lead us to conclude that the gm/Id method and integer encoding are quite useful to accelerate the convergence of the evolutionary algorithm NSGA-II, while the second optimisation stage guarantees robustness of the feasible solutions to PVT variations.

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

PubMed

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.

A supportive architecture for CFD-based design optimisation

NASA Astrophysics Data System (ADS)

Li, Ni; Su, Zeya; Bi, Zhuming; Tian, Chao; Ren, Zhiming; Gong, Guanghong

2014-03-01

Multi-disciplinary design optimisation (MDO) is one of critical methodologies to the implementation of enterprise systems (ES). MDO requiring the analysis of fluid dynamics raises a special challenge due to its extremely intensive computation. The rapid development of computational fluid dynamic (CFD) technique has caused a rise of its applications in various fields. Especially for the exterior designs of vehicles, CFD has become one of the three main design tools comparable to analytical approaches and wind tunnel experiments. CFD-based design optimisation is an effective way to achieve the desired performance under the given constraints. However, due to the complexity of CFD, integrating with CFD analysis in an intelligent optimisation algorithm is not straightforward. It is a challenge to solve a CFD-based design problem, which is usually with high dimensions, and multiple objectives and constraints. It is desirable to have an integrated architecture for CFD-based design optimisation. However, our review on existing works has found that very few researchers have studied on the assistive tools to facilitate CFD-based design optimisation. In the paper, a multi-layer architecture and a general procedure are proposed to integrate different CFD toolsets with intelligent optimisation algorithms, parallel computing technique and other techniques for efficient computation. In the proposed architecture, the integration is performed either at the code level or data level to fully utilise the capabilities of different assistive tools. Two intelligent algorithms are developed and embedded with parallel computing. These algorithms, together with the supportive architecture, lay a solid foundation for various applications of CFD-based design optimisation. To illustrate the effectiveness of the proposed architecture and algorithms, the case studies on aerodynamic shape design of a hypersonic cruising vehicle are provided, and the result has shown that the proposed architecture and developed algorithms have performed successfully and efficiently in dealing with the design optimisation with over 200 design variables.

Modelling and strategy optimisation for a kind of networked evolutionary games with memories under the bankruptcy mechanism

NASA Astrophysics Data System (ADS)

Fu, Shihua; Li, Haitao; Zhao, Guodong

2018-05-01

This paper investigates the evolutionary dynamic and strategy optimisation for a kind of networked evolutionary games whose strategy updating rules incorporate 'bankruptcy' mechanism, and the situation that each player's bankruptcy is due to the previous continuous low profits gaining from the game is considered. First, by using semi-tensor product of matrices method, the evolutionary dynamic of this kind of games is expressed as a higher order logical dynamic system and then converted into its algebraic form, based on which, the evolutionary dynamic of the given games can be discussed. Second, the strategy optimisation problem is investigated, and some free-type control sequences are designed to maximise the total payoff of the whole game. Finally, an illustrative example is given to show that our new results are very effective.

Simulation and Optimization of an Astrophotonic Reformatter

NASA Astrophysics Data System (ADS)

Anagnos, Th; Harris, R. J.; Corrigan, M. K.; Reeves, A. P.; Townson, M. J.; MacLachlan, D. G.; Thomson, R. R.; Morris, T. J.; Schwab, C.; Quirrenbach, A.

2018-05-01

Image slicing is a powerful technique in astronomy. It allows the instrument designer to reduce the slit width of the spectrograph, increasing spectral resolving power whilst retaining throughput. Conventionally this is done using bulk optics, such as mirrors and prisms, however more recently astrophotonic components known as PLs and photonic reformatters have also been used. These devices reformat the MM input light from a telescope into SM outputs, which can then be re-arranged to suit the spectrograph. The PD is one such device, designed to reduce the dependence of spectrograph size on telescope aperture and eliminate modal noise. We simulate the PD, by optimising the throughput and geometrical design using Soapy and BeamProp. The simulated device shows a transmission between 8 and 20 %, depending upon the type of AO correction applied, matching the experimental results well. We also investigate our idealised model of the PD and show that the barycentre of the slit varies only slightly with time, meaning that the modal noise contribution is very low when compared to conventional fibre systems. We further optimise our model device for both higher throughput and reduced modal noise. This device improves throughput by 6.4 % and reduces the movement of the slit output by 50%, further improving stability. This shows the importance of properly simulating such devices, including atmospheric effects. Our work complements recent work in the field and is essential for optimising future photonic reformatters.

A hybrid neural learning algorithm using evolutionary learning and derivative free local search method.

PubMed

Ghosh, Ranadhir; Yearwood, John; Ghosh, Moumita; Bagirov, Adil

2006-06-01

In this paper we investigate a hybrid model based on the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. Also we discuss different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient method has the advantage of being able to jump over many local minima and find very deep local minima. However, earlier research has shown that a good starting point for the discrete gradient method can improve the quality of the solution point. Evolutionary algorithms are best suited for global optimisation problems. Nevertheless they are cursed with longer training times and often unsuitable for real world application. For optimisation problems such as weight optimisation for ANNs in real world applications the dimensions are large and time complexity is critical. Hence the idea of a hybrid model can be a suitable option. In this paper we propose different fusion strategies for hybrid models combining the evolutionary strategy with the discrete gradient method to obtain an optimal solution much quicker. Three different fusion strategies are discussed: a linear hybrid model, an iterative hybrid model and a restricted local search hybrid model. Comparative results on a range of standard datasets are provided for different fusion hybrid models.

Optimisation of an analytical method and results from the inter-laboratory comparison of the migration of regulated substances from food packaging into the new mandatory European Union simulant for dry foodstuffs.

PubMed

Jakubowska, Natalia; Beldì, Giorgia; Peychès Bach, Aurélie; Simoneau, Catherine

2014-01-01

This paper presents the outcome of the development, optimisation and validation at European Union level of an analytical method for using poly(2,6-diphenyl phenylene oxide--PPPO), which is stipulated in Regulation (EU) No. 10/2011, as food simulant E for testing specific migration from plastics into dry foodstuffs. Two methods for fortifying respectively PPPO and a low-density polyethylene (LDPE) film with surrogate substances that are relevant to food contact were developed. A protocol for cleaning the PPPO and an efficient analytical method were developed for the quantification of butylhydroxytoluene (BHT), benzophenone (BP), diisobutylphthalate (DiBP), bis(2-ethylhexyl) adipate (DEHA) and 1,2-cyclohexanedicarboxylic acid, diisononyl ester (DINCH) from PPPO. A protocol for a migration test from plastics using small migration cells was also developed. The method was validated by an inter-laboratory comparison (ILC) with 16 national reference laboratories for food contact materials in the European Union. This allowed for the first time data to be obtained on the precision and laboratory performance of both migration and quantification. The results showed that the validation ILC was successful even when taking into account the complexity of the exercise. The results showed that the method performance was 7-9% repeatability standard deviation (rSD) for most substances (regardless of concentration), with 12% rSD for the high level of BHT and for DiBP at very low levels. The reproducibility standard deviation results for the 16 European Union laboratories were in the range of 20-30% for the quantification from PPPO (for the three levels of concentrations of the five substances) and 15-40% from migration experiments from the fortified plastic at 60°C for 10 days and subsequent quantification. Considering the lack of data previously available in the literature, this work has demonstrated that the validation of a method is possible both for migration from a film and for quantification into a corresponding simulant for specific migration.

Exploring the Role of Genetic Algorithms and Artificial Neural Networks for Interpolation of Elevation in Geoinformation Models

NASA Astrophysics Data System (ADS)

Bagheri, H.; Sadjadi, S. Y.; Sadeghian, S.

2013-09-01

One of the most significant tools to study many engineering projects is three-dimensional modelling of the Earth that has many applications in the Geospatial Information System (GIS), e.g. creating Digital Train Modelling (DTM). DTM has numerous applications in the fields of sciences, engineering, design and various project administrations. One of the most significant events in DTM technique is the interpolation of elevation to create a continuous surface. There are several methods for interpolation, which have shown many results due to the environmental conditions and input data. The usual methods of interpolation used in this study along with Genetic Algorithms (GA) have been optimised and consisting of polynomials and the Inverse Distance Weighting (IDW) method. In this paper, the Artificial Intelligent (AI) techniques such as GA and Neural Networks (NN) are used on the samples to optimise the interpolation methods and production of Digital Elevation Model (DEM). The aim of entire interpolation methods is to evaluate the accuracy of interpolation methods. Universal interpolation occurs in the entire neighbouring regions can be suggested for larger regions, which can be divided into smaller regions. The results obtained from applying GA and ANN individually, will be compared with the typical method of interpolation for creation of elevations. The resulting had performed that AI methods have a high potential in the interpolation of elevations. Using artificial networks algorithms for the interpolation and optimisation based on the IDW method with GA could be estimated the high precise elevations.

Integrated optimisation technique based on computer-aided capacity and safety evaluation for managing downstream lane-drop merging area of signalised junctions

NASA Astrophysics Data System (ADS)

Chen, CHAI; Yiik Diew, WONG

2017-02-01

This study provides an integrated strategy, encompassing microscopic simulation, safety assessment, and multi-attribute decision-making, to optimize traffic performance at downstream merging area of signalized intersections. A Fuzzy Cellular Automata (FCA) model is developed to replicate microscopic movement and merging behavior. Based on simulation experiment, the proposed FCA approach is able to provide capacity and safety evaluation of different traffic scenarios. The results are then evaluated through data envelopment analysis (DEA) and analytic hierarchy process (AHP). Optimized geometric layout and control strategies are then suggested for various traffic conditions. An optimal lane-drop distance that is dependent on traffic volume and speed limit can thus be established at the downstream merging area.

Using the Person-Based Approach to optimise a digital intervention for the management of hypertension

PubMed Central

Morton, Katherine; Band, Rebecca; van Woezik, Anne; Grist, Rebecca; McManus, Richard J.; Little, Paul; Yardley, Lucy

2018-01-01

Background For behaviour-change interventions to be successful they must be acceptable to users and overcome barriers to behaviour change. The Person-Based Approach can help to optimise interventions to maximise acceptability and engagement. This article presents a novel, efficient and systematic method that can be used as part of the Person-Based Approach to rapidly analyse data from development studies to inform intervention modifications. We describe how we used this approach to optimise a digital intervention for patients with hypertension (HOME BP), which aims to implement medication and lifestyle changes to optimise blood pressure control. Methods In study 1, hypertensive patients (N = 12) each participated in three think-aloud interviews, providing feedback on a prototype of HOME BP. In study 2 patients (N = 11) used HOME BP for three weeks and were then interviewed about their experiences. Studies 1 and 2 were used to identify detailed changes to the intervention content and potential barriers to engagement with HOME BP. In study 3 (N = 7) we interviewed hypertensive patients who were not interested in using an intervention like HOME BP to identify potential barriers to uptake, which informed modifications to our recruitment materials. Analysis in all three studies involved detailed tabulation of patient data and comparison to our modification criteria. Results Studies 1 and 2 indicated that the HOME BP procedures were generally viewed as acceptable and feasible, but also highlighted concerns about monitoring blood pressure correctly at home and making medication changes remotely. Patients in study 3 had additional concerns about the safety and security of the intervention. Modifications improved the acceptability of the intervention and recruitment materials. Conclusions This paper provides a detailed illustration of how to use the Person-Based Approach to refine a digital intervention for hypertension. The novel, efficient approach to analysis and criteria for deciding when to implement intervention modifications described here may be useful to others developing interventions. PMID:29723262

Analysis of the car body stability performance after coupler jack-knifing during braking

NASA Astrophysics Data System (ADS)

Guo, Lirong; Wang, Kaiyun; Chen, Zaigang; Shi, Zhiyong; Lv, Kaikai; Ji, Tiancheng

2018-06-01

This paper aims to improve car body stability performance by optimising locomotive parameters when coupler jack-knifing occurs during braking. In order to prevent car body instability behaviour caused by coupler jack-knifing, a multi-locomotive simulation model and a series of field braking tests are developed to analyse the influence of the secondary suspension and the secondary lateral stopper on the car body stability performance during braking. According to simulation and test results, increasing secondary lateral stiffness contributes to limit car body yaw angle during braking. However, it seriously affects the dynamic performance of the locomotive. For the secondary lateral stopper, its lateral stiffness and free clearance have a significant influence on improving the car body stability capacity, and have less effect on the dynamic performance of the locomotive. An optimised measure was proposed and adopted on the test locomotive. For the optimised locomotive, the lateral stiffness of secondary lateral stopper is increased to 7875 kN/m, while its free clearance is decreased to 10 mm. The optimised locomotive has excellent dynamic and safety performance. Comparing with the original locomotive, the maximum car body yaw angle and coupler rotation angle of the optimised locomotive were reduced by 59.25% and 53.19%, respectively, according to the practical application. The maximum derailment coefficient was 0.32, and the maximum wheelset lateral force was 39.5 kN. Hence, reasonable parameters of secondary lateral stopper can improve the car body stability capacity and the running safety of the heavy haul locomotive.

Extending the FairRoot framework to allow for simulation and reconstruction of free streaming data

NASA Astrophysics Data System (ADS)

Al-Turany, M.; Klein, D.; Manafov, A.; Rybalchenko, A.; Uhlig, F.

2014-06-01

The FairRoot framework is the standard framework for simulation, reconstruction and data analysis for the FAIR experiments. The framework is designed to optimise the accessibility for beginners and developers, to be flexible and to cope with future developments. FairRoot enhances the synergy between the different physics experiments. As a first step toward simulation of free streaming data, the time based simulation was introduced to the framework. The next step is the event source simulation. This is achieved via a client server system. After digitization the so called "samplers" can be started, where sampler can read the data of the corresponding detector from the simulation files and make it available for the reconstruction clients. The system makes it possible to develop and validate the online reconstruction algorithms. In this work, the design and implementation of the new architecture and the communication layer will be described.

Design of a compact antenna with flared groundplane for a wearable breast hyperthermia system.

PubMed

Curto, Sergio; Prakash, Punit

2015-01-01

Currently available microwave hyperthermia systems for breast cancer treatment do not conform to the intact breast and provide limited control of heating patterns, thereby hindering an effective treatment. A compact patch antenna with a flared groundplane that may be integrated within a wearable hyperthermia system for the treatment of the intact breast disease is proposed. A 3D simulation-based approach was employed to optimise the antenna design with the objective of maximising the hyperthermia treatment volume (41 °C iso-therm) while maintaining good impedance matching. The optimised antenna design was fabricated and experimentally evaluated with ex vivo tissue measurements. The optimised compact antenna yielded a -10 dB bandwidth of 90 MHz centred at 915 MHz, and was capable of creating hyperthermia treatment volumes up to 14.4 cm(3) (31 mm × 28 mm × 32 mm) with an input power of 15 W. Experimentally measured reflection coefficient and transient temperature profiles were in good agreement with simulated profiles. Variations of + 50% in blood perfusion yielded variations in the treatment volume up to 11.5%. When compared to an antenna with a similar patch element employing a conventional rectangular groundplane, the antenna with flared groundplane afforded 22.3% reduction in required power levels to reach the same temperature, and yielded 2.4 times larger treatment volumes. The proposed patch antenna with a flared groundplane may be integrated within a wearable applicator for hyperthermia treatment of intact breast targets and has the potential to improve efficiency, increase patient comfort, and ultimately clinical outcomes.

Simulation modelling as a tool for knowledge mobilisation in health policy settings: a case study protocol.

PubMed

Freebairn, L; Atkinson, J; Kelly, P; McDonnell, G; Rychetnik, L

2016-09-21

Evidence-informed decision-making is essential to ensure that health programs and services are effective and offer value for money; however, barriers to the use of evidence persist. Emerging systems science approaches and advances in technology are providing new methods and tools to facilitate evidence-based decision-making. Simulation modelling offers a unique tool for synthesising and leveraging existing evidence, data and expert local knowledge to examine, in a robust, low risk and low cost way, the likely impact of alternative policy and service provision scenarios. This case study will evaluate participatory simulation modelling to inform the prevention and management of gestational diabetes mellitus (GDM). The risks associated with GDM are well recognised; however, debate remains regarding diagnostic thresholds and whether screening and treatment to reduce maternal glucose levels reduce the associated risks. A diagnosis of GDM may provide a leverage point for multidisciplinary lifestyle modification interventions. This research will apply and evaluate a simulation modelling approach to understand the complex interrelation of factors that drive GDM rates, test options for screening and interventions, and optimise the use of evidence to inform policy and program decision-making. The study design will use mixed methods to achieve the objectives. Policy, clinical practice and research experts will work collaboratively to develop, test and validate a simulation model of GDM in the Australian Capital Territory (ACT). The model will be applied to support evidence-informed policy dialogues with diverse stakeholders for the management of GDM in the ACT. Qualitative methods will be used to evaluate simulation modelling as an evidence synthesis tool to support evidence-based decision-making. Interviews and analysis of workshop recordings will focus on the participants' engagement in the modelling process; perceived value of the participatory process, perceived commitment, influence and confidence of stakeholders in implementing policy and program decisions identified in the modelling process; and the impact of the process in terms of policy and program change. The study will generate empirical evidence on the feasibility and potential value of simulation modelling to support knowledge mobilisation and consensus building in health settings.

A methodology for the optimisation of a mm-wave scanner

NASA Astrophysics Data System (ADS)

Stec, L. Zoë; Podd, Frank J. W.; Peyton, Anthony J.

2016-10-01

The need to detect non-metallic items under clothes to prevent terrorism at transport hubs is becoming vital. Millimetre wave technology is able to penetrate clothing, yet able to interact with objects concealed underneath. This paper considers active illumination using multiple transmitter and receiver antennas. The positioning of these antennas must achieve full body coverage, whilst minimising the number of antenna elements and the number of required measurements. It sets out a rapid simulation methodology, based on the Kirchhoff equations, to explore different scenarios for scanner architecture optimisation. The paper assumes that the electromagnetic waves used are at lower frequencies (say, 10-30 GHz) where the body temperature does not need to be considered. This range allows better penetration of clothing than higher frequencies, yet still provides adequate resolution. Since passengers vary greatly in shape and size, the system needs to be able to work well with a range of body morphologies. Thus we have used two very differently shaped avatars to test the portal simulations. This simulation tool allows many different avatars to be generated quickly. Findings from these simulations indicated that the dimensions of the avatar did indeed have an effect on the pattern of illumination, and that the data for each antenna pair can easily be combined to compare different antenna geometries for a given portal architecture, resulting in useful insights into antenna placement. The data generated could be analysed both quantitatively and qualitatively, at various levels of scale.

Robustness analysis of bogie suspension components Pareto optimised values

NASA Astrophysics Data System (ADS)

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.

Limitations of subjective cognitive load measures in simulation-based procedural training.

PubMed

Naismith, Laura M; Cheung, Jeffrey J H; Ringsted, Charlotte; Cavalcanti, Rodrigo B

2015-08-01

The effective implementation of cognitive load theory (CLT) to optimise the instructional design of simulation-based training requires sensitive and reliable measures of cognitive load. This mixed-methods study assessed relationships between commonly used measures of total cognitive load and the extent to which these measures reflected participants' experiences of cognitive load in simulation-based procedural skills training. Two groups of medical residents (n = 38) completed three questionnaires after participating in simulation-based procedural skills training sessions: the Paas Cognitive Load Scale; the NASA Task Load Index (TLX), and a cognitive load component (CLC) questionnaire we developed to assess total cognitive load as the sum of intrinsic load (how complex the task is), extraneous load (how the task is presented) and germane load (how the learner processes the task for learning). We calculated Pearson's correlation coefficients to assess agreement among these instruments. Group interviews explored residents' perceptions about how the simulation sessions contributed to their total cognitive load. Interviews were audio-recorded, transcribed and subjected to qualitative content analysis. Total cognitive load scores differed significantly according to the instrument used to assess them. In particular, there was poor agreement between the Paas Scale and the TLX. Quantitative and qualitative findings supported intrinsic cognitive load as synonymous with mental effort (Paas Scale), mental demand (TLX) and task difficulty and complexity (CLC questionnaire). Additional qualitative themes relating to extraneous and germane cognitive loads were not reflected in any of the questionnaires. The Paas Scale, TLX and CLC questionnaire appear to be interchangeable as measures of intrinsic cognitive load, but not of total cognitive load. A more complete understanding of the sources of extraneous and germane cognitive loads in simulation-based training contexts is necessary to determine how best to measure and assess their effects on learning and performance outcomes. © 2015 John Wiley & Sons Ltd.

SASS Applied to Optimum Work Roll Profile Selection in the Hot Rolling of Wide Steel

NASA Astrophysics Data System (ADS)

Nolle, Lars

The quality of steel strip produced in a wide strip rolling mill depends heavily on the careful selection of initial ground work roll profiles for each of the mill stands in the finishing train. In the past, these profiles were determined by human experts, based on their knowledge and experience. In previous work, the profiles were successfully optimised using a self-organising migration algorithm (SOMA). In this research, SASS, a novel heuristic optimisation algorithm that has only one control parameter, has been used to find the optimum profiles for a simulated rolling mill. The resulting strip quality produced using the profiles found by SASS is compared with results from previous work and the quality produced using the original profile specifications. The best set of profiles found by SASS clearly outperformed the original set and performed equally well as SOMA without the need of finding a suitable set of control parameters.

Optimisation of flavour ester biosynthesis in an aqueous system of coconut cream and fusel oil catalysed by lipase.

PubMed

Sun, Jingcan; Yu, Bin; Curran, Philip; Liu, Shao-Quan

2012-12-15

Coconut cream and fusel oil, two low-cost natural substances, were used as starting materials for the biosynthesis of flavour-active octanoic acid esters (ethyl-, butyl-, isobutyl- and (iso)amyl octanoate) using lipase Palatase as the biocatalyst. The Taguchi design method was used for the first time to optimize the biosynthesis of esters by a lipase in an aqueous system of coconut cream and fusel oil. Temperature, time and enzyme amount were found to be statistically significant factors and the optimal conditions were determined to be as follows: temperature 30°C, fusel oil concentration 9% (v/w), reaction time 24h, pH 6.2 and enzyme amount 0.26 g. Under the optimised conditions, a yield of 14.25mg/g (based on cream weight) and signal-to-noise (S/N) ratio of 23.07 dB were obtained. The results indicate that the Taguchi design method was an efficient and systematic approach to the optimisation of lipase-catalysed biological processes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Warranty optimisation based on the prediction of costs to the manufacturer using neural network model and Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Stamenkovic, Dragan D.; Popovic, Vladimir M.

2015-02-01

Warranty is a powerful marketing tool, but it always involves additional costs to the manufacturer. In order to reduce these costs and make use of warranty's marketing potential, the manufacturer needs to master the techniques for warranty cost prediction according to the reliability characteristics of the product. In this paper a combination free replacement and pro rata warranty policy is analysed as warranty model for one type of light bulbs. Since operating conditions have a great impact on product reliability, they need to be considered in such analysis. A neural network model is used to predict light bulb reliability characteristics based on the data from the tests of light bulbs in various operating conditions. Compared with a linear regression model used in the literature for similar tasks, the neural network model proved to be a more accurate method for such prediction. Reliability parameters obtained in this way are later used in Monte Carlo simulation for the prediction of times to failure needed for warranty cost calculation. The results of the analysis make possible for the manufacturer to choose the optimal warranty policy based on expected product operating conditions. In such a way, the manufacturer can lower the costs and increase the profit.

Radiation exposure in X-ray-based imaging techniques used in osteoporosis

PubMed Central

Adams, Judith E.; Guglielmi, Giuseppe; Link, Thomas M.

2010-01-01

Recent advances in medical X-ray imaging have enabled the development of new techniques capable of assessing not only bone quantity but also structure. This article provides (a) a brief review of the current X-ray methods used for quantitative assessment of the skeleton, (b) data on the levels of radiation exposure associated with these methods and (c) information about radiation safety issues. Radiation doses associated with dual-energy X-ray absorptiometry are very low. However, as with any X-ray imaging technique, each particular examination must always be clinically justified. When an examination is justified, the emphasis must be on dose optimisation of imaging protocols. Dose optimisation is more important for paediatric examinations because children are more vulnerable to radiation than adults. Methods based on multi-detector CT (MDCT) are associated with higher radiation doses. New 3D volumetric hip and spine quantitative computed tomography (QCT) techniques and high-resolution MDCT for evaluation of bone structure deliver doses to patients from 1 to 3 mSv. Low-dose protocols are needed to reduce radiation exposure from these methods and minimise associated health risks. PMID:20559834

Assessing the spatial impact of climate on wheat productivity and the potential value of climate forecasts at a regional level

NASA Astrophysics Data System (ADS)

Wang, Enli; Xu, J.; Jiang, Q.; Austin, J.

2009-03-01

Quantification of the spatial impact of climate on crop productivity and the potential value of seasonal climate forecasts can effectively assist the strategic planning of crop layout and help to understand to what extent climate risk can be managed through responsive management strategies at a regional level. A simulation study was carried out to assess the climate impact on the performance of a dryland wheat-fallow system and the potential value of seasonal climate forecasts in nitrogen management in the Murray-Darling Basin (MDB) of Australia. Daily climate data (1889-2002) from 57 stations were used with the agricultural systems simulator (APSIM) to simulate wheat productivity and nitrogen requirement as affected by climate. On a good soil, simulated grain yield ranged from <2 t/ha in west inland to >7 t/ha in the east border regions. Optimal nitrogen rates ranged from <60 kgN/ha/yr to >200 kgN/ha/yr. Simulated gross margin was in the range of -20/ha to 700/ha, increasing eastwards. Wheat yield was closely related to rainfall in the growing season and the stored soil moisture at sowing time. The impact of stored soil moisture increased from southwest to northeast. Simulated annual deep drainage ranged from zero in western inland to >200 mm in the east. Nitrogen management, optimised based on ‘perfect’ knowledge of daily weather in the coming season, could add value of 26˜79/ha compared to management optimised based on historical climate, with the maximum occurring in central to western part of MDB. It would also reduce the nitrogen application by 5˜25 kgN/ha in the main cropping areas. Comparison of simulation results with the current land use mapping in MDB revealed that the western boundary of the current cropping zone approximated the isolines of 160 mm of growing season rainfall, 2.5t/ha of wheat grain yield, and 150/ha of gross margin in QLD and NSW. In VIC and SA, the 160-mm isohyets corresponded relatively lower simulated yield due to less stored soil water. Impacts of other factors like soil types were also discussed.

The solution of target assignment problem in command and control decision-making behaviour simulation

NASA Astrophysics Data System (ADS)

Li, Ni; Huai, Wenqing; Wang, Shaodan

2017-08-01

C2 (command and control) has been understood to be a critical military component to meet an increasing demand for rapid information gathering and real-time decision-making in a dynamically changing battlefield environment. In this article, to improve a C2 behaviour model's reusability and interoperability, a behaviour modelling framework was proposed to specify a C2 model's internal modules and a set of interoperability interfaces based on the C-BML (coalition battle management language). WTA (weapon target assignment) is a typical C2 autonomous decision-making behaviour modelling problem. Different from most WTA problem descriptions, here sensors were considered to be available resources of detection and the relationship constraints between weapons and sensors were also taken into account, which brought it much closer to actual application. A modified differential evolution (MDE) algorithm was developed to solve this high-dimension optimisation problem and obtained an optimal assignment plan with high efficiency. In case study, we built a simulation system to validate the proposed C2 modelling framework and interoperability interface specification. Also, a new optimisation solution was used to solve the WTA problem efficiently and successfully.

An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing.

PubMed

Wu, Zujian; Pang, Wei; Coghill, George M

2015-01-01

Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.

Suspension parameter estimation in the frequency domain using a matrix inversion approach

NASA Astrophysics Data System (ADS)

Thite, A. N.; Banvidi, S.; Ibicek, T.; Bennett, L.

2011-12-01

The dynamic lumped parameter models used to optimise the ride and handling of a vehicle require base values of the suspension parameters. These parameters are generally experimentally identified. The accuracy of identified parameters can depend on the measurement noise and the validity of the model used. The existing publications on suspension parameter identification are generally based on the time domain and use a limited degree of freedom. Further, the data used are either from a simulated 'experiment' or from a laboratory test on an idealised quarter or a half-car model. In this paper, a method is developed in the frequency domain which effectively accounts for the measurement noise. Additional dynamic constraining equations are incorporated and the proposed formulation results in a matrix inversion approach. The nonlinearities in damping are estimated, however, using a time-domain approach. Full-scale 4-post rig test data of a vehicle are used. The variations in the results are discussed using the modal resonant behaviour. Further, a method is implemented to show how the results can be improved when the matrix inverted is ill-conditioned. The case study shows a good agreement between the estimates based on the proposed frequency-domain approach and measurable physical parameters.

Experimental research and numerical optimisation of multi-point sheet metal forming implementation using a solid elastic cushion system

NASA Astrophysics Data System (ADS)

Tolipov, A. A.; Elghawail, A.; Shushing, S.; Pham, D.; Essa, K.

2017-09-01

There is a growing demand for flexible manufacturing techniques that meet the rapid changes in customer needs. A finite element analysis numerical optimisation technique was used to optimise the multi-point sheet forming process. Multi-point forming (MPF) is a flexible sheet metal forming technique where the same tool can be readily changed to produce different parts. The process suffers from some geometrical defects such as wrinkling and dimpling, which have been found to be the cause of the major surface quality problems. This study investigated the influence of parameters such as the elastic cushion hardness, blank holder force, coefficient of friction, cushion thickness and radius of curvature, on the quality of parts formed in a flexible multi-point stamping die. For those reasons, in this investigation, a multipoint forming stamping process using a blank holder was carried out in order to study the effects of the wrinkling, dimpling, thickness variation and forming force. The aim was to determine the optimum values of these parameters. Finite element modelling (FEM) was employed to simulate the multi-point forming of hemispherical shapes. Using the response surface method, the effects of process parameters on wrinkling, maximum deviation from the target shape and thickness variation were investigated. The results show that elastic cushion with proper thickness and polyurethane with the hardness of Shore A90. It has also been found that the application of lubrication cans improve the shape accuracy of the formed workpiece. These final results were compared with the numerical simulation results of the multi-point forming for hemispherical shapes using a blank-holder and it was found that using cushion hardness realistic to reduce wrinkling and maximum deviation.

The seasonal behaviour of carbon fluxes in the Amazon: fusion of FLUXNET data and the ORCHIDEE model

NASA Astrophysics Data System (ADS)

Verbeeck, H.; Peylin, P.; Bacour, C.; Ciais, P.

2009-04-01

Eddy covariance measurements at the Santarém (km 67) site revealed an unexpected seasonal pattern in carbon fluxes which could not be simulated by existing state-of-the-art global ecosystem models (Saleska et al., Sciece 2003). An unexpected high carbon uptake was measured during dry season. In contrast, carbon release was observed in the wet season. There are several possible (combined) underlying mechanisms of this phenomenon: (1) an increased soil respiration due to soil moisture in the wet season, (2) increased photosynthesis during the dry season due to deep rooting, hydraulic lift, increased radiation and/or a leaf flush. The objective of this study is to optimise the ORCHIDEE model using eddy covariance data in order to be able to mimic the seasonal response of carbon fluxes to dry/wet conditions in tropical forest ecosystems. By doing this, we try to identify the underlying mechanisms of this seasonal response. The ORCHIDEE model is a state of the art mechanistic global vegetation model that can be run at local or global scale. It calculates the carbon and water cycle in the different soil and vegetation pools and resolves the diurnal cycle of fluxes. ORCHIDEE is built on the concept of plant functional types (PFT) to describe vegetation. To bring the different carbon pool sizes to realistic values, spin-up runs are used. ORCHIDEE uses climate variables as drivers together with a number of ecosystem parameters that have been assessed from laboratory and in situ experiments. These parameters are still associated with a large uncertainty and may vary between and within PFTs in a way that is currently not informed or captured by the model. Recently, the development of assimilation techniques allows the objective use of eddy covariance data to improve our knowledge of these parameters in a statistically coherent approach. We use a Bayesian optimisation approach. This approach is based on the minimization of a cost function containing the mismatch between simulated model output and observations as well as the mismatch between a priori and optimized parameters. The parameters can be optimized on different time scales (annually, monthly, daily). For this study the model is optimised at local scale for 5 eddy flux sites: 4 sites in Brazil and one in French Guyana. The seasonal behaviour of C fluxes in response to wet and dry conditions differs among these sites. Key processes that are optimised include: the effect of the soil water on heterotrophic soil respiration, the effect of soil water availability on stomatal conductance and photosynthesis, and phenology. By optimising several key parameters we could improve the simulation of the seasonal pattern of NEE significantly. Nevertheless, posterior parameters should be interpreted with care, because resulting parameter values might compensate for uncertainties on the model structure or other parameters. Moreover, several critical issues appeared during this study e.g. how to assimilate latent and sensible heat data, when the energy balance is not closed in the data? Optimisation of the Q10 parameter showed that on some sites respiration was not sensitive at all to temperature, which show only small variations in this region. Considering this, one could question the reliability of the partitioned fluxes (GPP/Reco) at these sites. This study also tests if there is coherence between optimised parameter values of different sites within the tropical forest PFT and if the forward model response to climate variations is similar between sites.

Systemic solutions for multi-benefit water and environmental management.

PubMed

Everard, Mark; McInnes, Robert

2013-09-01

The environmental and financial costs of inputs to, and unintended consequences arising from narrow consideration of outputs from, water and environmental management technologies highlight the need for low-input solutions that optimise outcomes across multiple ecosystem services. Case studies examining the inputs and outputs associated with several ecosystem-based water and environmental management technologies reveal a range from those that differ little from conventional electro-mechanical engineering techniques through methods, such as integrated constructed wetlands (ICWs), designed explicitly as low-input systems optimising ecosystem service outcomes. All techniques present opportunities for further optimisation of outputs, and hence for greater cumulative public value. We define 'systemic solutions' as "…low-input technologies using natural processes to optimise benefits across the spectrum of ecosystem services and their beneficiaries". They contribute to sustainable development by averting unintended negative impacts and optimising benefits to all ecosystem service beneficiaries, increasing net economic value. Legacy legislation addressing issues in a fragmented way, associated 'ring-fenced' budgets and established management assumptions represent obstacles to implementing 'systemic solutions'. However, flexible implementation of legacy regulations recognising their primary purpose, rather than slavish adherence to detailed sub-clauses, may achieve greater overall public benefit through optimisation of outcomes across ecosystem services. Systemic solutions are not a panacea if applied merely as 'downstream' fixes, but are part of, and a means to accelerate, broader culture change towards more sustainable practice. This necessarily entails connecting a wider network of interests in the formulation and design of mutually-beneficial systemic solutions, including for example spatial planners, engineers, regulators, managers, farming and other businesses, and researchers working on ways to quantify and optimise delivery of ecosystem services. Copyright © 2013 Elsevier B.V. All rights reserved.

Simulation studies promote technological development of radiofrequency phased array hyperthermia.

PubMed

Wust, P; Seebass, M; Nadobny, J; Deuflhard, P; Mönich, G; Felix, R

1996-01-01

A treatment planning program package for radiofrequency hyperthermia has been developed. It consists of software modules for processing three-dimensional computerized tomography (CT) data sets, manual segmentation, generation of tetrahedral grids, numerical calculation and optimisation of three-dimensional E field distributions using a volume surface integral equation algorithm as well as temperature distributions using an adaptive multilevel finite-elements code, and graphical tools for simultaneous representation of CT data and simulation results. Heat treatments are limited by hot spots in healthy tissues caused by E field maxima at electrical interfaces (bone/muscle). In order to reduce or avoid hot spots suitable objective functions are derived from power deposition patterns and temperature distributions, and are utilised to optimise antenna parameters (phases, amplitudes). The simulation and optimisation tools have been applied to estimate the improvements that could be reached by upgrades of the clinically used SIGMA-60 applicator (consisting of a single ring of four antenna pairs). The investigated upgrades are increased number of antennas and channels (triple-ring of 3 x 8 antennas and variation of antenna inclination. Significant improvement of index temperatures (1-2 degrees C) is achieved by upgrading the single ring to a triple ring with free phase selection for every antenna or antenna pair. Antenna amplitudes and inclinations proved as less important parameters.

Hybrid real-code ant colony optimisation for constrained mechanical design

NASA Astrophysics Data System (ADS)

Pholdee, Nantiwat; Bureerat, Sujin

2016-01-01

This paper proposes a hybrid meta-heuristic based on integrating a local search simplex downhill (SDH) method into the search procedure of real-code ant colony optimisation (ACOR). This hybridisation leads to five hybrid algorithms where a Monte Carlo technique, a Latin hypercube sampling technique (LHS) and a translational propagation Latin hypercube design (TPLHD) algorithm are used to generate an initial population. Also, two numerical schemes for selecting an initial simplex are investigated. The original ACOR and its hybrid versions along with a variety of established meta-heuristics are implemented to solve 17 constrained test problems where a fuzzy set theory penalty function technique is used to handle design constraints. The comparative results show that the hybrid algorithms are the top performers. Using the TPLHD technique gives better results than the other sampling techniques. The hybrid optimisers are a powerful design tool for constrained mechanical design problems.

Optimisation of the imaging and dosimetric characteristics of an electronic portal imaging device employing plastic scintillating fibres using Monte Carlo simulations.

PubMed

Blake, S J; McNamara, A L; Vial, P; Holloway, L; Kuncic, Z

2014-11-21

A Monte Carlo model of a novel electronic portal imaging device (EPID) has been developed using Geant4 and its performance for imaging and dosimetry applications in radiotherapy has been characterised. The EPID geometry is based on a physical prototype under ongoing investigation and comprises an array of plastic scintillating fibres in place of the metal plate/phosphor screen in standard EPIDs. Geometrical and optical transport parameters were varied to investigate their impact on imaging and dosimetry performance. Detection efficiency was most sensitive to variations in fibre length, achieving a peak value of 36% at 50 mm using 400 keV x-rays for the lengths considered. Increases in efficiency for longer fibres were partially offset by reductions in sensitivity. Removing the extra-mural absorber surrounding individual fibres severely decreased the modulation transfer function (MTF), highlighting its importance in maximising spatial resolution. Field size response and relative dose profile simulations demonstrated a water-equivalent dose response and thus the prototype's suitability for dosimetry applications. Element-to-element mismatch between scintillating fibres and underlying photodiode pixels resulted in a reduced MTF for high spatial frequencies and quasi-periodic variations in dose profile response. This effect is eliminated when fibres are precisely matched to underlying pixels. Simulations strongly suggest that with further optimisation, this prototype EPID may be capable of simultaneous imaging and dosimetry in radiotherapy.

An effective method to increase bandwidth of EIK at 0.34 THz

NASA Astrophysics Data System (ADS)

Li, Shuang; Wang, Guangqiang; Wang, Dongyang

2018-02-01

To increase the bandwidth of Extended Interaction Klystron (EIK) at 0.34 THz, the method of staggered tuning on cavities' configurations is proposed. Based on the analysis of phase relationship between gap voltage and the bunched beam, the buncher cavities in EIK are reasonably staggered-tuned to achieve various resonance frequencies, which is helpful to flat the gain response of the whole device. The characteristics of output cavities with different numbers of gaps are then researched and the issue of start current for the self-oscillation mode is also involved, leading to the optimum number of gaps to enhance the interaction and avoid the instability. By comparing the performances of various typical stagger-tuned models, the final configuration is accordingly confirmed. Particle-in-cell simulation is eventually applied to study performance of the optimised structure, whose gain is 34.8 dB in peak and -3 dB bandwidth reaches about 500 MHz, which is double that of the synchronous-tuned structure.

Validation of Analytical Damping Ratio by Fatigue Stress Limit

NASA Astrophysics Data System (ADS)

Foong, Faruq Muhammad; Chung Ket, Thein; Beng Lee, Ooi; Aziz, Abdul Rashid Abdul

2018-03-01

The optimisation process of a vibration energy harvester is usually restricted to experimental approaches due to the lack of an analytical equation to describe the damping of a system. This study derives an analytical equation, which describes the first mode damping ratio of a clamp-free cantilever beam under harmonic base excitation by combining the transverse equation of motion of the beam with the damping-stress equation. This equation, as opposed to other common damping determination methods, is independent of experimental inputs or finite element simulations and can be solved using a simple iterative convergence method. The derived equation was determined to be correct for cases when the maximum bending stress in the beam is below the fatigue limit stress of the beam. However, an increasing trend in the error between the experiment and the analytical results were observed at high stress levels. Hence, the fatigue limit stress was used as a parameter to define the validity of the analytical equation.

Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context

NASA Astrophysics Data System (ADS)

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. A brief overview of atmospheric and weather modelling is also included. Key equations describing the optimality criteria are presented, with a focus on the latest advancements in the respective application areas. In the sixth section, a number of MOTO implementations in the CNS+A systems context are mentioned with relevant simulation case studies addressing different operational tasks. The final section draws some conclusions and outlines guidelines for future research on MOTO and associated CNS+A system implementations.

Statistical atmospheric inversion of local gas emissions by coupling the tracer release technique and local-scale transport modelling: a test case with controlled methane emissions

NASA Astrophysics Data System (ADS)

Ars, Sébastien; Broquet, Grégoire; Yver Kwok, Camille; Roustan, Yelva; Wu, Lin; Arzoumanian, Emmanuel; Bousquet, Philippe

2017-12-01

This study presents a new concept for estimating the pollutant emission rates of a site and its main facilities using a series of atmospheric measurements across the pollutant plumes. This concept combines the tracer release method, local-scale atmospheric transport modelling and a statistical atmospheric inversion approach. The conversion between the controlled emission and the measured atmospheric concentrations of the released tracer across the plume places valuable constraints on the atmospheric transport. This is used to optimise the configuration of the transport model parameters and the model uncertainty statistics in the inversion system. The emission rates of all sources are then inverted to optimise the match between the concentrations simulated with the transport model and the pollutants' measured atmospheric concentrations, accounting for the transport model uncertainty. In principle, by using atmospheric transport modelling, this concept does not strongly rely on the good colocation between the tracer and pollutant sources and can be used to monitor multiple sources within a single site, unlike the classical tracer release technique. The statistical inversion framework and the use of the tracer data for the configuration of the transport and inversion modelling systems should ensure that the transport modelling errors are correctly handled in the source estimation. The potential of this new concept is evaluated with a relatively simple practical implementation based on a Gaussian plume model and a series of inversions of controlled methane point sources using acetylene as a tracer gas. The experimental conditions are chosen so that they are suitable for the use of a Gaussian plume model to simulate the atmospheric transport. In these experiments, different configurations of methane and acetylene point source locations are tested to assess the efficiency of the method in comparison to the classic tracer release technique in coping with the distances between the different methane and acetylene sources. The results from these controlled experiments demonstrate that, when the targeted and tracer gases are not well collocated, this new approach provides a better estimate of the emission rates than the tracer release technique. As an example, the relative error between the estimated and actual emission rates is reduced from 32 % with the tracer release technique to 16 % with the combined approach in the case of a tracer located 60 m upwind of a single methane source. Further studies and more complex implementations with more advanced transport models and more advanced optimisations of their configuration will be required to generalise the applicability of the approach and strengthen its robustness.

Model-Free Machine Learning in Biomedicine: Feasibility Study in Type 1 Diabetes

PubMed Central

Daskalaki, Elena; Diem, Peter; Mougiakakou, Stavroula G.

2016-01-01

Although reinforcement learning (RL) is suitable for highly uncertain systems, the applicability of this class of algorithms to medical treatment may be limited by the patient variability which dictates individualised tuning for their usually multiple algorithmic parameters. This study explores the feasibility of RL in the framework of artificial pancreas development for type 1 diabetes (T1D). In this approach, an Actor-Critic (AC) learning algorithm is designed and developed for the optimisation of insulin infusion for personalised glucose regulation. AC optimises the daily basal insulin rate and insulin:carbohydrate ratio for each patient, on the basis of his/her measured glucose profile. Automatic, personalised tuning of AC is based on the estimation of information transfer (IT) from insulin to glucose signals. Insulin-to-glucose IT is linked to patient-specific characteristics related to total daily insulin needs and insulin sensitivity (SI). The AC algorithm is evaluated using an FDA-accepted T1D simulator on a large patient database under a complex meal protocol, meal uncertainty and diurnal SI variation. The results showed that 95.66% of time was spent in normoglycaemia in the presence of meal uncertainty and 93.02% when meal uncertainty and SI variation were simultaneously considered. The time spent in hypoglycaemia was 0.27% in both cases. The novel tuning method reduced the risk of severe hypoglycaemia, especially in patients with low SI. PMID:27441367

Accelerating clinical development of HIV vaccine strategies: methodological challenges and considerations in constructing an optimised multi-arm phase I/II trial design.

PubMed

Richert, Laura; Doussau, Adélaïde; Lelièvre, Jean-Daniel; Arnold, Vincent; Rieux, Véronique; Bouakane, Amel; Lévy, Yves; Chêne, Geneviève; Thiébaut, Rodolphe

2014-02-26

Many candidate vaccine strategies against human immunodeficiency virus (HIV) infection are under study, but their clinical development is lengthy and iterative. To accelerate HIV vaccine development optimised trial designs are needed. We propose a randomised multi-arm phase I/II design for early stage development of several vaccine strategies, aiming at rapidly discarding those that are unsafe or non-immunogenic. We explored early stage designs to evaluate both the safety and the immunogenicity of four heterologous prime-boost HIV vaccine strategies in parallel. One of the vaccines used as a prime and boost in the different strategies (vaccine 1) has yet to be tested in humans, thus requiring a phase I safety evaluation. However, its toxicity risk is considered minimal based on data from similar vaccines. We newly adapted a randomised phase II trial by integrating an early safety decision rule, emulating that of a phase I study. We evaluated the operating characteristics of the proposed design in simulation studies with either a fixed-sample frequentist or a continuous Bayesian safety decision rule and projected timelines for the trial. We propose a randomised four-arm phase I/II design with two independent binary endpoints for safety and immunogenicity. Immunogenicity evaluation at trial end is based on a single-stage Fleming design per arm, comparing the observed proportion of responders in an immunogenicity screening assay to an unacceptably low proportion, without direct comparisons between arms. Randomisation limits heterogeneity in volunteer characteristics between arms. To avoid exposure of additional participants to an unsafe vaccine during the vaccine boost phase, an early safety decision rule is imposed on the arm starting with vaccine 1 injections. In simulations of the design with either decision rule, the risks of erroneous conclusions were controlled <15%. Flexibility in trial conduct is greater with the continuous Bayesian rule. A 12-month gain in timelines is expected by this optimised design. Other existing designs such as bivariate or seamless phase I/II designs did not offer a clear-cut alternative. By combining phase I and phase II evaluations in a multi-arm trial, the proposed optimised design allows for accelerating early stage clinical development of HIV vaccine strategies.

Simultaneous data pre-processing and SVM classification model selection based on a parallel genetic algorithm applied to spectroscopic data of olive oils.

PubMed

Devos, Olivier; Downey, Gerard; Duponchel, Ludovic

2014-04-01

Classification is an important task in chemometrics. For several years now, support vector machines (SVMs) have proven to be powerful for infrared spectral data classification. However such methods require optimisation of parameters in order to control the risk of overfitting and the complexity of the boundary. Furthermore, it is established that the prediction ability of classification models can be improved using pre-processing in order to remove unwanted variance in the spectra. In this paper we propose a new methodology based on genetic algorithm (GA) for the simultaneous optimisation of SVM parameters and pre-processing (GENOPT-SVM). The method has been tested for the discrimination of the geographical origin of Italian olive oil (Ligurian and non-Ligurian) on the basis of near infrared (NIR) or mid infrared (FTIR) spectra. Different classification models (PLS-DA, SVM with mean centre data, GENOPT-SVM) have been tested and statistically compared using McNemar's statistical test. For the two datasets, SVM with optimised pre-processing give models with higher accuracy than the one obtained with PLS-DA on pre-processed data. In the case of the NIR dataset, most of this accuracy improvement (86.3% compared with 82.8% for PLS-DA) occurred using only a single pre-processing step. For the FTIR dataset, three optimised pre-processing steps are required to obtain SVM model with significant accuracy improvement (82.2%) compared to the one obtained with PLS-DA (78.6%). Furthermore, this study demonstrates that even SVM models have to be developed on the basis of well-corrected spectral data in order to obtain higher classification rates. Copyright © 2013 Elsevier Ltd. All rights reserved.

Non-fragile observer-based output feedback control for polytopic uncertain system under distributed model predictive control approach

NASA Astrophysics Data System (ADS)

Zhu, Kaiqun; Song, Yan; Zhang, Sunjie; Zhong, Zhaozhun

2017-07-01

In this paper, a non-fragile observer-based output feedback control problem for the polytopic uncertain system under distributed model predictive control (MPC) approach is discussed. By decomposing the global system into some subsystems, the computation complexity is reduced, so it follows that the online designing time can be saved.Moreover, an observer-based output feedback control algorithm is proposed in the framework of distributed MPC to deal with the difficulties in obtaining the states measurements. In this way, the presented observer-based output-feedback MPC strategy is more flexible and applicable in practice than the traditional state-feedback one. What is more, the non-fragility of the controller has been taken into consideration in favour of increasing the robustness of the polytopic uncertain system. After that, a sufficient stability criterion is presented by using Lyapunov-like functional approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimisation subject to convex constraints. Finally, some simulation examples are employed to show the effectiveness of the method.

Optimisation of 12 MeV electron beam simulation using variance reduction technique

NASA Astrophysics Data System (ADS)

Jayamani, J.; Termizi, N. A. S. Mohd; Kamarulzaman, F. N. Mohd; Aziz, M. Z. Abdul

2017-05-01

Monte Carlo (MC) simulation for electron beam radiotherapy consumes a long computation time. An algorithm called variance reduction technique (VRT) in MC was implemented to speed up this duration. This work focused on optimisation of VRT parameter which refers to electron range rejection and particle history. EGSnrc MC source code was used to simulate (BEAMnrc code) and validate (DOSXYZnrc code) the Siemens Primus linear accelerator model with the non-VRT parameter. The validated MC model simulation was repeated by applying VRT parameter (electron range rejection) that controlled by global electron cut-off energy 1,2 and 5 MeV using 20 × 107 particle history. 5 MeV range rejection generated the fastest MC simulation with 50% reduction in computation time compared to non-VRT simulation. Thus, 5 MeV electron range rejection utilized in particle history analysis ranged from 7.5 × 107 to 20 × 107. In this study, 5 MeV electron cut-off with 10 × 107 particle history, the simulation was four times faster than non-VRT calculation with 1% deviation. Proper understanding and use of VRT can significantly reduce MC electron beam calculation duration at the same time preserving its accuracy.

An Optimised System for Generating Multi-Resolution Dtms Using NASA Mro Datasets

NASA Astrophysics Data System (ADS)

Tao, Y.; Muller, J.-P.; Sidiropoulos, P.; Veitch-Michaelis, J.; Yershov, V.

2016-06-01

Within the EU FP-7 iMars project, a fully automated multi-resolution DTM processing chain, called Co-registration ASP-Gotcha Optimised (CASP-GO) has been developed, based on the open source NASA Ames Stereo Pipeline (ASP). CASP-GO includes tiepoint based multi-resolution image co-registration and an adaptive least squares correlation-based sub-pixel refinement method called Gotcha. The implemented system guarantees global geo-referencing compliance with respect to HRSC (and thence to MOLA), provides refined stereo matching completeness and accuracy based on the ASP normalised cross-correlation. We summarise issues discovered from experimenting with the use of the open-source ASP DTM processing chain and introduce our new working solutions. These issues include global co-registration accuracy, de-noising, dealing with failure in matching, matching confidence estimation, outlier definition and rejection scheme, various DTM artefacts, uncertainty estimation, and quality-efficiency trade-offs.

Using multimedia tools and high-fidelity simulations to improve medical students' resuscitation performance: an observational study

PubMed Central

Wang, Candice; Huang, Chin-Chou; Lin, Shing-Jong; Chen, Jaw-Wen

2016-01-01

Objectives The goal of our study was to shed light on educational methods to strengthen medical students' cardiopulmonary resuscitation (CPR) leadership and team skills in order to optimise CPR understanding and success using didactic videos and high-fidelity simulations. Design An observational study. Setting A tertiary medical centre in Northern Taiwan. Participants A total of 104 5–7th year medical students, including 72 men and 32 women. Interventions We provided the medical students with a 2-hour training session on advanced CPR. During each class, we divided the students into 1–2 groups; each group consisted of 4–6 team members. Medical student teams were trained by using either method A or B. Method A started with an instructional CPR video followed by a first CPR simulation. Method B started with a first CPR simulation followed by an instructional CPR video. All students then participated in a second CPR simulation. Outcome measures Student teams were assessed with checklist rating scores in leadership, teamwork and team member skills, global rating scores by an attending physician and video-recording evaluation by 2 independent individuals. Results The 104 medical students were divided into 22 teams. We trained 11 teams using method A and 11 using method B. Total second CPR simulation scores were significantly higher than first CPR simulation scores in leadership (p<0.001), teamwork (p<0.001) and team member skills (p<0.001). For methods A and B students' first CPR simulation scores were similar, but method A students' second CPR simulation scores were significantly higher than those of method B in leadership skills (p=0.034), specifically in the support subcategory (p=0.049). Conclusions Although both teaching strategies improved leadership, teamwork and team member performance, video exposure followed by CPR simulation further increased students' leadership skills compared with CPR simulation followed by video exposure. PMID:27678539

SIMS(DAIRY): a modelling framework to identify sustainable dairy farms in the UK. Framework description and test for organic systems and N fertiliser optimisation.

PubMed

Del Prado, A; Misselbrook, T; Chadwick, D; Hopkins, A; Dewhurst, R J; Davison, P; Butler, A; Schröder, J; Scholefield, D

2011-09-01

Multiple demands are placed on farming systems today. Society, national legislation and market forces seek what could be seen as conflicting outcomes from our agricultural systems, e.g. food quality, affordable prices, a healthy environmental, consideration of animal welfare, biodiversity etc., Many of these demands, or desirable outcomes, are interrelated, so reaching one goal may often compromise another and, importantly, pose a risk to the economic viability of the farm. SIMS(DAIRY), a farm-scale model, was used to explore this complexity for dairy farm systems. SIMS(DAIRY) integrates existing approaches to simulate the effect of interactions between farm management, climate and soil characteristics on losses of nitrogen, phosphorus and carbon. The effects on farm profitability and attributes of biodiversity, milk quality, soil quality and animal welfare are also included. SIMS(DAIRY) can also be used to optimise fertiliser N. In this paper we discuss some limitations and strengths of using SIMS(DAIRY) compared to other modelling approaches and propose some potential improvements. Using the model we evaluated the sustainability of organic dairy systems compared with conventional dairy farms under non-optimised and optimised fertiliser N use. Model outputs showed for example, that organic dairy systems based on grass-clover swards and maize silage resulted in much smaller total GHG emissions per l of milk and slightly smaller losses of NO(3) leaching and NO(x) emissions per l of milk compared with the grassland/maize-based conventional systems. These differences were essentially because the conventional systems rely on indirect energy use for 'fixing' N compared with biological N fixation for the organic systems. SIMS(DAIRY) runs also showed some other potential benefits from the organic systems compared with conventional systems in terms of financial performance and soil quality and biodiversity scores. Optimisation of fertiliser N timings and rates showed a considerable scope to reduce the (GHG emissions per l milk too). Copyright © 2011 Elsevier B.V. All rights reserved.

Study on optimal configuration of the grid-connected wind-solar-battery hybrid power system

NASA Astrophysics Data System (ADS)

Ma, Gang; Xu, Guchao; Ju, Rong; Wu, Tiantian

2017-08-01

The capacity allocation of each energy unit in the grid-connected wind-solar-battery hybrid power system is a significant segment in system design. In this paper, taking power grid dispatching into account, the research priorities are as follows: (1) We establish the mathematic models of each energy unit in the hybrid power system. (2) Based on dispatching of the power grid, energy surplus rate, system energy volatility and total cost, we establish the evaluation system for the wind-solar-battery power system and use a number of different devices as the constraint condition. (3) Based on an improved Genetic algorithm, we put forward a multi-objective optimisation algorithm to solve the optimal configuration problem in the hybrid power system, so we can achieve the high efficiency and economy of the grid-connected hybrid power system. The simulation result shows that the grid-connected wind-solar-battery hybrid power system has a higher comprehensive performance; the method of optimal configuration in this paper is useful and reasonable.

Detection of bremsstrahlung radiation of 90Sr-90Y for emergency lung counting.

PubMed

Ho, A; Hakmana Witharana, S S; Jonkmans, G; Li, L; Surette, R A; Dubeau, J; Dai, X

2012-09-01

This study explores the possibility of developing a field-deployable (90)Sr detector for rapid lung counting in emergency situations. The detection of beta-emitters (90)Sr and its daughter (90)Y inside the human lung via bremsstrahlung radiation was performed using a 3″ × 3″ NaI(Tl) crystal detector and a polyethylene-encapsulated source to emulate human lung tissue. The simulation results show that this method is a viable technique for detecting (90)Sr with a minimum detectable activity (MDA) of 1.07 × 10(4) Bq, using a realistic dual-shielded detector system in a 0.25-µGy h(-1) background field for a 100-s scan. The MDA is sufficiently sensitive to meet the requirement for emergency lung counting of Type S (90)Sr intake. The experimental data were verified using Monte Carlo calculations, including an estimate for internal bremsstrahlung, and an optimisation of the detector geometry was performed. Optimisations in background reduction techniques and in the electronic acquisition systems are suggested.

Efficient methods for enol phosphate synthesis using carbon-centred magnesium bases.

PubMed

Kerr, William J; Lindsay, David M; Patel, Vipulkumar K; Rajamanickam, Muralikrishnan

2015-10-28

Efficient conversion of ketones into kinetic enol phosphates under mild and accessible conditions has been realised using the developed methods with di-tert-butylmagnesium and bismesitylmagnesium. Optimisation of the quench protocol resulted in high yields of enol phosphates from a range of cyclohexanones and aryl methyl ketones, with tolerance of a range of additional functional units.

Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations

NASA Astrophysics Data System (ADS)

Hoogenboom, J. Eduard; Dufek, Jan

2014-06-01

This paper describes an optimised iteration scheme for the number of neutron histories and the relaxation factor in successive iterations of coupled Monte Carlo and thermal-hydraulic reactor calculations based on the stochastic iteration method. The scheme results in an increasing number of neutron histories for the Monte Carlo calculation in successive iteration steps and a decreasing relaxation factor for the spatial power distribution to be used as input to the thermal-hydraulics calculation. The theoretical basis is discussed in detail and practical consequences of the scheme are shown, among which a nearly linear increase per iteration of the number of cycles in the Monte Carlo calculation. The scheme is demonstrated for a full PWR type fuel assembly. Results are shown for the axial power distribution during several iteration steps. A few alternative iteration method are also tested and it is concluded that the presented iteration method is near optimal.

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

NASA Astrophysics Data System (ADS)

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.

Adaptive neuro fuzzy inference system-based power estimation method for CMOS VLSI circuits

NASA Astrophysics Data System (ADS)

Vellingiri, Govindaraj; Jayabalan, Ramesh

2018-03-01

Recent advancements in very large scale integration (VLSI) technologies have made it feasible to integrate millions of transistors on a single chip. This greatly increases the circuit complexity and hence there is a growing need for less-tedious and low-cost power estimation techniques. The proposed work employs Back-Propagation Neural Network (BPNN) and Adaptive Neuro Fuzzy Inference System (ANFIS), which are capable of estimating the power precisely for the complementary metal oxide semiconductor (CMOS) VLSI circuits, without requiring any knowledge on circuit structure and interconnections. The ANFIS to power estimation application is relatively new. Power estimation using ANFIS is carried out by creating initial FIS modes using hybrid optimisation and back-propagation (BP) techniques employing constant and linear methods. It is inferred that ANFIS with the hybrid optimisation technique employing the linear method produces better results in terms of testing error that varies from 0% to 0.86% when compared to BPNN as it takes the initial fuzzy model and tunes it by means of a hybrid technique combining gradient descent BP and mean least-squares optimisation algorithms. ANFIS is the best suited for power estimation application with a low RMSE of 0.0002075 and a high coefficient of determination (R) of 0.99961.

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

NASA Astrophysics Data System (ADS)

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.

Optimisation of process parameters on thin shell part using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Faiz, J. M.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Rashidi, M. M.

2017-09-01

This study is carried out to focus on optimisation of process parameters by simulation using Autodesk Moldflow Insight (AMI) software. The process parameters are taken as the input in order to analyse the warpage value which is the output in this study. There are some significant parameters that have been used which are melt temperature, mould temperature, packing pressure, and cooling time. A plastic part made of Polypropylene (PP) has been selected as the study part. Optimisation of process parameters is applied in Design Expert software with the aim to minimise the obtained warpage value. Response Surface Methodology (RSM) has been applied in this study together with Analysis of Variance (ANOVA) in order to investigate the interactions between parameters that are significant to the warpage value. Thus, the optimised warpage value can be obtained using the model designed using RSM due to its minimum error value. This study comes out with the warpage value improved by using RSM.

Natural Erosion of Sandstone as Shape Optimisation.

PubMed

Ostanin, Igor; Safonov, Alexander; Oseledets, Ivan

2017-12-11

Natural arches, pillars and other exotic sandstone formations have always been attracting attention for their unusual shapes and amazing mechanical balance that leave a strong impression of intelligent design rather than the result of a stochastic process. It has been recently demonstrated that these shapes could have been the result of the negative feedback between stress and erosion that originates in fundamental laws of friction between the rock's constituent particles. Here we present a deeper analysis of this idea and bridge it with the approaches utilized in shape and topology optimisation. It appears that the processes of natural erosion, driven by stochastic surface forces and Mohr-Coulomb law of dry friction, can be viewed within the framework of local optimisation for minimum elastic strain energy. Our hypothesis is confirmed by numerical simulations of the erosion using the topological-shape optimisation model. Our work contributes to a better understanding of stochastic erosion and feasible landscape formations that could be found on Earth and beyond.

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

NASA Technical Reports Server (NTRS)

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.

Subject Specific Optimisation of the Stiffness of Footwear Material for Maximum Plantar Pressure Reduction.

PubMed

Chatzistergos, Panagiotis E; Naemi, Roozbeh; Healy, Aoife; Gerth, Peter; Chockalingam, Nachiappan

2017-08-01

Current selection of cushioning materials for therapeutic footwear and orthoses is based on empirical and anecdotal evidence. The aim of this investigation is to assess the biomechanical properties of carefully selected cushioning materials and to establish the basis for patient-specific material optimisation. For this purpose, bespoke cushioning materials with qualitatively similar mechanical behaviour but different stiffness were produced. Healthy volunteers were asked to stand and walk on materials with varying stiffness and their capacity for pressure reduction was assessed. Mechanical testing using a surrogate heel model was employed to investigate the effect of loading on optimum stiffness. Results indicated that optimising the stiffness of cushioning materials improved pressure reduction during standing and walking by at least 16 and 19% respectively. Moreover, the optimum stiffness was strongly correlated to body mass (BM) and body mass index (BMI), with stiffer materials needed in the case of people with higher BM or BMI. Mechanical testing confirmed that optimum stiffness increases with the magnitude of compressive loading. For the first time, this study provides quantitative data to support the importance of stiffness optimisation in cushioning materials and sets the basis for methods to inform optimum material selection in the clinic.

Computational aero-acoustics for fan duct propagation and radiation. Current status and application to turbofan liner optimisation

NASA Astrophysics Data System (ADS)

Astley, R. J.; Sugimoto, R.; Mustafi, P.

2011-08-01

Novel techniques are presented to reduce noise from turbofan aircraft engines by optimising the acoustic treatment in engine ducts. The application of Computational Aero-Acoustics (CAA) to predict acoustic propagation and absorption in turbofan ducts is reviewed and a critical assessment of performance indicates that validated and accurate techniques are now available for realistic engine predictions. A procedure for integrating CAA methods with state of the art optimisation techniques is proposed in the remainder of the article. This is achieved by embedding advanced computational methods for noise prediction within automated and semi-automated optimisation schemes. Two different strategies are described and applied to realistic nacelle geometries and fan sources to demonstrate the feasibility of this approach for industry scale problems.

A universal preconditioner for simulating condensed phase materials.

PubMed

Packwood, David; Kermode, James; Mones, Letif; Bernstein, Noam; Woolley, John; Gould, Nicholas; Ortner, Christoph; Csányi, Gábor

2016-04-28

We introduce a universal sparse preconditioner that accelerates geometry optimisation and saddle point search tasks that are common in the atomic scale simulation of materials. Our preconditioner is based on the neighbourhood structure and we demonstrate the gain in computational efficiency in a wide range of materials that include metals, insulators, and molecular solids. The simple structure of the preconditioner means that the gains can be realised in practice not only when using expensive electronic structure models but also for fast empirical potentials. Even for relatively small systems of a few hundred atoms, we observe speedups of a factor of two or more, and the gain grows with system size. An open source Python implementation within the Atomic Simulation Environment is available, offering interfaces to a wide range of atomistic codes.

A universal preconditioner for simulating condensed phase materials

NASA Astrophysics Data System (ADS)

Packwood, David; Kermode, James; Mones, Letif; Bernstein, Noam; Woolley, John; Gould, Nicholas; Ortner, Christoph; Csányi, Gábor

2016-04-01

We introduce a universal sparse preconditioner that accelerates geometry optimisation and saddle point search tasks that are common in the atomic scale simulation of materials. Our preconditioner is based on the neighbourhood structure and we demonstrate the gain in computational efficiency in a wide range of materials that include metals, insulators, and molecular solids. The simple structure of the preconditioner means that the gains can be realised in practice not only when using expensive electronic structure models but also for fast empirical potentials. Even for relatively small systems of a few hundred atoms, we observe speedups of a factor of two or more, and the gain grows with system size. An open source Python implementation within the Atomic Simulation Environment is available, offering interfaces to a wide range of atomistic codes.

Topology optimisation for natural convection problems

NASA Astrophysics Data System (ADS)

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

2014-12-01

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 for designing heat sink geometries cooled by natural convection and micropumps powered by natural convection.

Recovery of human DNA profiles from poached deer remains part 2: improved recovery protocol without the need for LCN analysis.

PubMed

Tobe, Shanan S; Bailey, Stuart; Govan, James; Welch, Lindsey A

2013-03-01

Although poaching is a common wildlife crime, the high and prohibitive cost of specialised animal testing means that many cases are left un-investigated. We previously described a novel approach to wildlife crime investigation that looked at the identification of human DNA on poached animal remains (Tobe, Govan and Welch, 2011). Human DNA was successfully isolated and amplified from simulated poaching incidents, however a low template protocol was required which made this method unsuitable for use in many laboratories. We now report on an optimised recovery and amplification protocol which removes the need for low template analysis. Samples from 10 deer (40 samples total - one from each leg) analysed in the original study were re-analysed in the current study with an additional 11 deer samples. Four samples analysed using Chelex did not show any results and a new method was devised whereby the available DNA was concentrated. By combining the DNA extracts from all tapings of the same deer remains followed by concentration, the recovered quantity of human DNA was found to be 29.5pg±43.2pg, 31× greater than the previous study. The use of the Investigator Decaplex SE (QIAGEN) STR kit provided better results in the form of more complete profiles than did the AmpFℓSTR® SGM Plus® kit at 30cycles (Applied Biosystems). Re-analysis of the samples from the initial study using the new, optimised protocol resulted in an average increase of 18% of recovered alleles. Over 17 samples, 71% of the samples analysed using the optimised protocol showed sufficient amplification for comparison to a reference profile and gave match probabilities ranging from 7.7690×10(-05) to 2.2706×10(-14). The removal of low template analysis means this optimised method provides evidence of high probative value and is suitable for immediate use in forensic laboratories. All methods and techniques used are standard and are compatible with current SOPs. As no high cost non-human DNA analysis is required the overall process is no more expensive than the investigation of other volume crime samples. The technique is suitable for immediate use in poaching incidents. Copyright © 2012 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

Modelling and Analysis of a New Piezoelectric Dynamic Balance Regulator

PubMed Central

Du, Zhe; Mei, Xue-Song; Xu, Mu-Xun

2012-01-01

In this paper, a new piezoelectric dynamic balance regulator, which can be used in motorised spindle systems, is presented. The dynamic balancing adjustment mechanism is driven by an in-plane bending vibration from an annular piezoelectric stator excited by a high-frequency sinusoidal input voltage. This device has different construction, characteristics and operating principles than a conventional balance regulator. In this work, a dynamic model of the regulator is first developed using a detailed analytical method. Thereafter, MATLAB is employed to numerically simulate the relations between the dominant parameters and the characteristics of the regulator based on thedynamic model. Finally, experimental measurements are used to certify the validity of the dynamic model. Consequently, the mathematical model presented and analysed in this paper can be used as a tool for optimising the design of a piezoelectric dynamic balance regulator during steady state operation. PMID:23202182

Global sensitivity analysis of a filtration model for submerged anaerobic membrane bioreactors (AnMBR).

PubMed

Robles, A; Ruano, M V; Ribes, J; Seco, A; Ferrer, J

2014-04-01

The results of a global sensitivity analysis of a filtration model for submerged anaerobic MBRs (AnMBRs) are assessed in this paper. This study aimed to (1) identify the less- (or non-) influential factors of the model in order to facilitate model calibration and (2) validate the modelling approach (i.e. to determine the need for each of the proposed factors to be included in the model). The sensitivity analysis was conducted using a revised version of the Morris screening method. The dynamic simulations were conducted using long-term data obtained from an AnMBR plant fitted with industrial-scale hollow-fibre membranes. Of the 14 factors in the model, six were identified as influential, i.e. those calibrated using off-line protocols. A dynamic calibration (based on optimisation algorithms) of these influential factors was conducted. The resulting estimated model factors accurately predicted membrane performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

Geo-information processing service composition for concurrent tasks: A QoS-aware game theory approach

NASA Astrophysics Data System (ADS)

Li, Haifeng; Zhu, Qing; Yang, Xiaoxia; Xu, Linrong

2012-10-01

Typical characteristics of remote sensing applications are concurrent tasks, such as those found in disaster rapid response. The existing composition approach to geographical information processing service chain, searches for an optimisation solution and is what can be deemed a "selfish" way. This way leads to problems of conflict amongst concurrent tasks and decreases the performance of all service chains. In this study, a non-cooperative game-based mathematical model to analyse the competitive relationships between tasks, is proposed. A best response function is used, to assure each task maintains utility optimisation by considering composition strategies of other tasks and quantifying conflicts between tasks. Based on this, an iterative algorithm that converges to Nash equilibrium is presented, the aim being to provide good convergence and maximise the utilisation of all tasks under concurrent task conditions. Theoretical analyses and experiments showed that the newly proposed method, when compared to existing service composition methods, has better practical utility in all tasks.

Choosing the appropriate forecasting model for predictive parameter control.

PubMed

Aleti, Aldeida; Moser, Irene; Meedeniya, Indika; Grunske, Lars

2014-01-01

All commonly used stochastic optimisation algorithms have to be parameterised to perform effectively. Adaptive parameter control (APC) is an effective method used for this purpose. APC repeatedly adjusts parameter values during the optimisation process for optimal algorithm performance. The assignment of parameter values for a given iteration is based on previously measured performance. In recent research, time series prediction has been proposed as a method of projecting the probabilities to use for parameter value selection. In this work, we examine the suitability of a variety of prediction methods for the projection of future parameter performance based on previous data. All considered prediction methods have assumptions the time series data has to conform to for the prediction method to provide accurate projections. Looking specifically at parameters of evolutionary algorithms (EAs), we find that all standard EA parameters with the exception of population size conform largely to the assumptions made by the considered prediction methods. Evaluating the performance of these prediction methods, we find that linear regression provides the best results by a very small and statistically insignificant margin. Regardless of the prediction method, predictive parameter control outperforms state of the art parameter control methods when the performance data adheres to the assumptions made by the prediction method. When a parameter's performance data does not adhere to the assumptions made by the forecasting method, the use of prediction does not have a notable adverse impact on the algorithm's performance.

End-to-end System Performance Simulation: A Data-Centric Approach

NASA Astrophysics Data System (ADS)

Guillaume, Arnaud; Laffitte de Petit, Jean-Luc; Auberger, Xavier

2013-08-01

In the early times of space industry, the feasibility of Earth observation missions was directly driven by what could be achieved by the satellite. It was clear to everyone that the ground segment would be able to deal with the small amount of data sent by the payload. Over the years, the amounts of data processed by the spacecrafts have been increasing drastically, leading to put more and more constraints on the ground segment performances - and in particular on timeliness. Nowadays, many space systems require high data throughputs and short response times, with information coming from multiple sources and involving complex algorithms. It has become necessary to perform thorough end-to-end analyses of the full system in order to optimise its cost and efficiency, but even sometimes to assess the feasibility of the mission. This paper presents a novel framework developed by Astrium Satellites in order to meet these needs of timeliness evaluation and optimisation. This framework, named ETOS (for “End-to-end Timeliness Optimisation of Space systems”), provides a modelling process with associated tools, models and GUIs. These are integrated thanks to a common data model and suitable adapters, with the aim of building suitable space systems simulators of the full end-to-end chain. A big challenge of such environment is to integrate heterogeneous tools (each one being well-adapted to part of the chain) into a relevant timeliness simulation.

Dual ant colony operational modal analysis parameter estimation method

NASA Astrophysics Data System (ADS)

Sitarz, Piotr; Powałka, Bartosz

2018-01-01

Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

A study of lateral fall-off (penumbra) optimisation for pencil beam scanning (PBS) proton therapy

NASA Astrophysics Data System (ADS)

Winterhalter, C.; Lomax, A.; Oxley, D.; Weber, D. C.; Safai, S.

2018-01-01

The lateral fall-off is crucial for sparing organs at risk in proton therapy. It is therefore of high importance to minimize the penumbra for pencil beam scanning (PBS). Three optimisation approaches are investigated: edge-collimated uniformly weighted spots (collimation), pencil beam optimisation of uncollimated pencil beams (edge-enhancement) and the optimisation of edge collimated pencil beams (collimated edge-enhancement). To deliver energies below 70 MeV, these strategies are evaluated in combination with the following pre-absorber methods: field specific fixed thickness pre-absorption (fixed), range specific, fixed thickness pre-absorption (automatic) and range specific, variable thickness pre-absorption (variable). All techniques are evaluated by Monte Carlo simulated square fields in a water tank. For a typical air gap of 10 cm, without pre-absorber collimation reduces the penumbra only for water equivalent ranges between 4-11 cm by up to 2.2 mm. The sharpest lateral fall-off is achieved through collimated edge-enhancement, which lowers the penumbra down to 2.8 mm. When using a pre-absorber, the sharpest fall-offs are obtained when combining collimated edge-enhancement with a variable pre-absorber. For edge-enhancement and large air gaps, it is crucial to minimize the amount of material in the beam. For small air gaps however, the superior phase space of higher energetic beams can be employed when more material is used. In conclusion, collimated edge-enhancement combined with the variable pre-absorber is the recommended setting to minimize the lateral penumbra for PBS. Without collimator, it would be favourable to use a variable pre-absorber for large air gaps and an automatic pre-absorber for small air gaps.

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

PubMed

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.

Optimisation of process parameters on thin shell part using response surface methodology (RSM) and genetic algorithm (GA)

NASA Astrophysics Data System (ADS)

Faiz, J. M.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

2017-09-01

This study conducts the simulation on optimisation of injection moulding process parameters using Autodesk Moldflow Insight (AMI) software. This study has applied some process parameters which are melt temperature, mould temperature, packing pressure, and cooling time in order to analyse the warpage value of the part. Besides, a part has been selected to be studied which made of Polypropylene (PP). The combination of the process parameters is analysed using Analysis of Variance (ANOVA) and the optimised value is obtained using Response Surface Methodology (RSM). The RSM as well as Genetic Algorithm are applied in Design Expert software in order to minimise the warpage value. The outcome of this study shows that the warpage value improved by using RSM and GA.

Fabrication of Organic Radar Absorbing Materials: A Report on the TIF Project

DTIC Science & Technology

2005-05-01

thickness, permittivity and permeability. The ability to measure the permittivity and permeability is an essential requirement for designing an optimised...absorber. And good optimisations codes are required in order to achieve the best possible absorber designs . In this report, the results from a...through measurement of their conductivity and permittivity at microwave frequencies. Methods were then developed for optimising the design of

Simulation of longitudinal dynamics of long freight trains in positioning operations

NASA Astrophysics Data System (ADS)

Qi, Zhaohui; Huang, Zhihao; Kong, Xianchao

2012-09-01

Positioning operations are performed in a railway goods yard, in which the freight train is pulled precisely at a specific point by a positioner. The positioner moves strictly according to the predesigned speed and provides all the traction and braking forces which are highly dependent on the longitudinal dynamic response. In order to improve the efficiency and protect the wagons from damage during positioning operations, the design speed of the positioner has to be optimised based on the simulation of longitudinal train dynamics. However, traditional models of longitudinal train dynamics are not accurate enough in some aspects. In this study, we make some changes in the traditional theory to make it suitable for the study of long freight trains in positioning operations. In the proposed method, instead of the traction force on the train, the motion of the positioner is assumed to be known; more importantly, the traditional draft gear model with nonlinear spring and linear damping is replaced by a more detailed model based on the achievement of contact and impact mechanics; the switching effects of the resistance and the coupler slack are also taken into consideration. Numerical examples that deal with positioning operations on the straight lines, slope lines and curving lines are given.

Medicines optimisation: priorities and challenges.

PubMed

Kaufman, Gerri

2016-03-23

Medicines optimisation is promoted in a guideline published in 2015 by the National Institute for Health and Care Excellence. Four guiding principles underpin medicines optimisation: aim to understand the patient's experience; ensure evidence-based choice of medicines; ensure medicines use is as safe as possible; and make medicines optimisation part of routine practice. Understanding the patient experience is important to improve adherence to medication regimens. This involves communication, shared decision making and respect for patient preferences. Evidence-based choice of medicines is important for clinical and cost effectiveness. Systems and processes for the reporting of medicines-related safety incidents have to be improved if medicines use is to be as safe as possible. Ensuring safe practice in medicines use when patients are transferred between organisations, and managing the complexities of polypharmacy are imperative. A medicines use review can help to ensure that medicines optimisation forms part of routine practice.

A DNS Investigation of Non-Newtonian Turbulent Open Channel Flow

NASA Astrophysics Data System (ADS)

Guang, Raymond; Rudman, Murray; Chryss, Andrew; Slatter, Paul; Bhattacharya, Sati

2010-06-01

The flow of non-Newtonian fluids in open channels has great significance in many industrial settings from water treatment to mine waste disposal. The turbulent behaviour during transportation of these materials is of interest for many reasons, one of which is keeping settleable particles in suspension. The mechanism governing particle transport in turbulent flow has been studied in the past, but is not well understood. A better understanding of the mechanism operating in the turbulent flow of non-Newtonian suspensions in open channel would lead to improved design of many of the systems used in the mining and mineral processing industries. The objective of this paper is to introduce our work on the Direct Numerical Simulation of turbulent flow of non-Newtonian fluids in an open channel. The numerical method is based on spectral element/Fourier formulation. The flow simulation of a Herschel-Bulkley fluid agrees qualitatively with experimental results. The simulation results over-predict the flow velocity by approximately 15% for the cases considered, although the source of the discrepancy is difficult to ascertain. The effect of variation in yield stress and assumed flow depth are investigated and used to assess the sensitivity of the flow to these physical parameters. This methodology is seen to be useful in designing and optimising the transport of slurries in open channels.

The 5C Concept and 5S Principles in Inflammatory Bowel Disease Management

PubMed Central

Hibi, Toshifumi; Panaccione, Remo; Katafuchi, Miiko; Yokoyama, Kaoru; Watanabe, Kenji; Matsui, Toshiyuki; Matsumoto, Takayuki; Travis, Simon; Suzuki, Yasuo

2017-01-01

Abstract Background and Aims The international Inflammatory Bowel Disease [IBD] Expert Alliance initiative [2012–2015] served as a platform to define and support areas of best practice in IBD management to help improve outcomes for all patients with IBD. Methods During the programme, IBD specialists from around the world established by consensus two best practice charters: the 5S Principles and the 5C Concept. Results The 5S Principles were conceived to provide health care providers with key guidance for improving clinical practice based on best management approaches. They comprise the following categories: Stage the disease; Stratify patients; Set treatment goals; Select appropriate treatment; and Supervise therapy. Optimised management of patients with IBD based on the 5S Principles can be achieved most effectively within an optimised clinical care environment. Guidance on optimising the clinical care setting in IBD management is provided through the 5C Concept, which encompasses: Comprehensive IBD care; Collaboration; Communication; Clinical nurse specialists; and Care pathways. Together, the 5C Concept and 5S Principles provide structured recommendations on organising the clinical care setting and developing best-practice approaches in IBD management. Conclusions Consideration and application of these two dimensions could help health care providers optimise their IBD centres and collaborate more effectively with their multidisciplinary team colleagues and patients, to provide improved IBD care in daily clinical practice. Ultimately, this could lead to improved outcomes for patients with IBD. PMID:28981622

Spoken language identification based on the enhanced self-adjusting extreme learning machine approach.

PubMed

Albadr, Musatafa Abbas Abbood; Tiun, Sabrina; Al-Dhief, Fahad Taha; Sammour, Mahmoud A M

2018-01-01

Spoken Language Identification (LID) is the process of determining and classifying natural language from a given content and dataset. Typically, data must be processed to extract useful features to perform LID. The extracting features for LID, based on literature, is a mature process where the standard features for LID have already been developed using Mel-Frequency Cepstral Coefficients (MFCC), Shifted Delta Cepstral (SDC), the Gaussian Mixture Model (GMM) and ending with the i-vector based framework. However, the process of learning based on extract features remains to be improved (i.e. optimised) to capture all embedded knowledge on the extracted features. The Extreme Learning Machine (ELM) is an effective learning model used to perform classification and regression analysis and is extremely useful to train a single hidden layer neural network. Nevertheless, the learning process of this model is not entirely effective (i.e. optimised) due to the random selection of weights within the input hidden layer. In this study, the ELM is selected as a learning model for LID based on standard feature extraction. One of the optimisation approaches of ELM, the Self-Adjusting Extreme Learning Machine (SA-ELM) is selected as the benchmark and improved by altering the selection phase of the optimisation process. The selection process is performed incorporating both the Split-Ratio and K-Tournament methods, the improved SA-ELM is named Enhanced Self-Adjusting Extreme Learning Machine (ESA-ELM). The results are generated based on LID with the datasets created from eight different languages. The results of the study showed excellent superiority relating to the performance of the Enhanced Self-Adjusting Extreme Learning Machine LID (ESA-ELM LID) compared with the SA-ELM LID, with ESA-ELM LID achieving an accuracy of 96.25%, as compared to the accuracy of SA-ELM LID of only 95.00%.

Spoken language identification based on the enhanced self-adjusting extreme learning machine approach

PubMed Central

Tiun, Sabrina; AL-Dhief, Fahad Taha; Sammour, Mahmoud A. M.

2018-01-01

Spoken Language Identification (LID) is the process of determining and classifying natural language from a given content and dataset. Typically, data must be processed to extract useful features to perform LID. The extracting features for LID, based on literature, is a mature process where the standard features for LID have already been developed using Mel-Frequency Cepstral Coefficients (MFCC), Shifted Delta Cepstral (SDC), the Gaussian Mixture Model (GMM) and ending with the i-vector based framework. However, the process of learning based on extract features remains to be improved (i.e. optimised) to capture all embedded knowledge on the extracted features. The Extreme Learning Machine (ELM) is an effective learning model used to perform classification and regression analysis and is extremely useful to train a single hidden layer neural network. Nevertheless, the learning process of this model is not entirely effective (i.e. optimised) due to the random selection of weights within the input hidden layer. In this study, the ELM is selected as a learning model for LID based on standard feature extraction. One of the optimisation approaches of ELM, the Self-Adjusting Extreme Learning Machine (SA-ELM) is selected as the benchmark and improved by altering the selection phase of the optimisation process. The selection process is performed incorporating both the Split-Ratio and K-Tournament methods, the improved SA-ELM is named Enhanced Self-Adjusting Extreme Learning Machine (ESA-ELM). The results are generated based on LID with the datasets created from eight different languages. The results of the study showed excellent superiority relating to the performance of the Enhanced Self-Adjusting Extreme Learning Machine LID (ESA-ELM LID) compared with the SA-ELM LID, with ESA-ELM LID achieving an accuracy of 96.25%, as compared to the accuracy of SA-ELM LID of only 95.00%. PMID:29672546

Application of Three Existing Stope Boundary Optimisation Methods in an Operating Underground Mine

NASA Astrophysics Data System (ADS)

Erdogan, Gamze; Yavuz, Mahmut

2017-12-01

The underground mine planning and design optimisation process have received little attention because of complexity and variability of problems in underground mines. Although a number of optimisation studies and software tools are available and some of them, in special, have been implemented effectively to determine the ultimate-pit limits in an open pit mine, there is still a lack of studies for optimisation of ultimate stope boundaries in underground mines. The proposed approaches for this purpose aim at maximizing the economic profit by selecting the best possible layout under operational, technical and physical constraints. In this paper, the existing three heuristic techniques including Floating Stope Algorithm, Maximum Value Algorithm and Mineable Shape Optimiser (MSO) are examined for optimisation of stope layout in a case study. Each technique is assessed in terms of applicability, algorithm capabilities and limitations considering the underground mine planning challenges. Finally, the results are evaluated and compared.

Computer-aided diagnosis of melanoma using border and wavelet-based texture analysis.

PubMed

Garnavi, Rahil; Aldeen, Mohammad; Bailey, James

2012-11-01

This paper presents a novel computer-aided diagnosis system for melanoma. The novelty lies in the optimised selection and integration of features derived from textural, borderbased and geometrical properties of the melanoma lesion. The texture features are derived from using wavelet-decomposition, the border features are derived from constructing a boundaryseries model of the lesion border and analysing it in spatial and frequency domains, and the geometry features are derived from shape indexes. The optimised selection of features is achieved by using the Gain-Ratio method, which is shown to be computationally efficient for melanoma diagnosis application. Classification is done through the use of four classifiers; namely, Support Vector Machine, Random Forest, Logistic Model Tree and Hidden Naive Bayes. The proposed diagnostic system is applied on a set of 289 dermoscopy images (114 malignant, 175 benign) partitioned into train, validation and test image sets. The system achieves and accuracy of 91.26% and AUC value of 0.937, when 23 features are used. Other important findings include (i) the clear advantage gained in complementing texture with border and geometry features, compared to using texture information only, and (ii) higher contribution of texture features than border-based features in the optimised feature set.

Implementation study of wearable sensors for activity recognition systems.

PubMed

Rezaie, Hamed; Ghassemian, Mona

2015-08-01

This Letter investigates and reports on a number of activity recognition methods for a wearable sensor system. The authors apply three methods for data transmission, namely 'stream-based', 'feature-based' and 'threshold-based' scenarios to study the accuracy against energy efficiency of transmission and processing power that affects the mote's battery lifetime. They also report on the impact of variation of sampling frequency and data transmission rate on energy consumption of motes for each method. This study leads us to propose a cross-layer optimisation of an activity recognition system for provisioning acceptable levels of accuracy and energy efficiency.

Optimisation of nano-silica modified self-compacting high-Volume fly ash mortar

NASA Astrophysics Data System (ADS)

Achara, Bitrus Emmanuel; Mohammed, Bashar S.; Fadhil Nuruddin, Muhd

2017-05-01

Evaluation of the effects of nano-silica amount and superplasticizer (SP) dosage on the compressive strength, porosity and slump flow on high-volume fly ash self-consolidating mortar was investigated. Multiobjective optimisation technique using Design-Expert software was applied to obtain solution based on desirability function that simultaneously optimises the variables and the responses. A desirability function of 0.811 gives the optimised solution. The experimental and predicted results showed minimal errors in all the measured responses.

Optimisation of solar synoptic observations

NASA Astrophysics Data System (ADS)

Klvaña, Miroslav; Sobotka, Michal; Švanda, Michal

2012-09-01

The development of instrumental and computer technologies is connected with steadily increasing needs for archiving of large data volumes. The current trend to meet this requirement includes the data compression and growth of storage capacities. This approach, however, has technical and practical limits. A further reduction of the archived data volume can be achieved by means of an optimisation of the archiving that consists in data selection without losing the useful information. We describe a method of optimised archiving of solar images, based on the selection of images that contain a new information. The new information content is evaluated by means of the analysis of changes detected in the images. We present characteristics of different kinds of image changes and divide them into fictitious changes with a disturbing effect and real changes that provide a new information. In block diagrams describing the selection and archiving, we demonstrate the influence of clouds, the recording of images during an active event on the Sun, including a period before the event onset, and the archiving of long-term history of solar activity. The described optimisation technique is not suitable for helioseismology, because it does not conserve the uniform time step in the archived sequence and removes the information about solar oscillations. In case of long-term synoptic observations, the optimised archiving can save a large amount of storage capacities. The actual capacity saving will depend on the setting of the change-detection sensitivity and on the capability to exclude the fictitious changes.

Power generation based on biomass by combined fermentation and gasification--a new concept derived from experiments and modelling.

PubMed

Methling, Torsten; Armbrust, Nina; Haitz, Thilo; Speidel, Michael; Poboss, Norman; Braun-Unkhoff, Marina; Dieter, Heiko; Kempter-Regel, Brigitte; Kraaij, Gerard; Schliessmann, Ursula; Sterr, Yasemin; Wörner, Antje; Hirth, Thomas; Riedel, Uwe; Scheffknecht, Günter

2014-10-01

A new concept is proposed for combined fermentation (two-stage high-load fermenter) and gasification (two-stage fluidised bed gasifier with CO2 separation) of sewage sludge and wood, and the subsequent utilisation of the biogenic gases in a hybrid power plant, consisting of a solid oxide fuel cell and a gas turbine. The development and optimisation of the important processes of the new concept (fermentation, gasification, utilisation) are reported in detail. For the gas production, process parameters were experimentally and numerically investigated to achieve high conversion rates of biomass. For the product gas utilisation, important combustion properties (laminar flame speed, ignition delay time) were analysed numerically to evaluate machinery operation (reliability, emissions). Furthermore, the coupling of the processes was numerically analysed and optimised by means of integration of heat and mass flows. The high, simulated electrical efficiency of 42% including the conversion of raw biomass is promising for future power generation by biomass. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spectral Band Selection for Urban Material Classification Using Hyperspectral Libraries

NASA Astrophysics Data System (ADS)

Le Bris, A.; Chehata, N.; Briottet, X.; Paparoditis, N.

2016-06-01

In urban areas, information concerning very high resolution land cover and especially material maps are necessary for several city modelling or monitoring applications. That is to say, knowledge concerning the roofing materials or the different kinds of ground areas is required. Airborne remote sensing techniques appear to be convenient for providing such information at a large scale. However, results obtained using most traditional processing methods based on usual red-green-blue-near infrared multispectral images remain limited for such applications. A possible way to improve classification results is to enhance the imagery spectral resolution using superspectral or hyperspectral sensors. In this study, it is intended to design a superspectral sensor dedicated to urban materials classification and this work particularly focused on the selection of the optimal spectral band subsets for such sensor. First, reflectance spectral signatures of urban materials were collected from 7 spectral libraires. Then, spectral optimization was performed using this data set. The band selection workflow included two steps, optimising first the number of spectral bands using an incremental method and then examining several possible optimised band subsets using a stochastic algorithm. The same wrapper relevance criterion relying on a confidence measure of Random Forests classifier was used at both steps. To cope with the limited number of available spectra for several classes, additional synthetic spectra were generated from the collection of reference spectra: intra-class variability was simulated by multiplying reference spectra by a random coefficient. At the end, selected band subsets were evaluated considering the classification quality reached using a rbf svm classifier. It was confirmed that a limited band subset was sufficient to classify common urban materials. The important contribution of bands from the Short Wave Infra-Red (SWIR) spectral domain (1000-2400 nm) to material classification was also shown.

Fallback options for airgap sensor fault of an electromagnetic suspension system

NASA Astrophysics Data System (ADS)

Michail, Konstantinos; Zolotas, Argyrios C.; Goodall, Roger M.

2013-06-01

The paper presents a method to recover the performance of an electromagnetic suspension under faulty airgap sensor. The proposed control scheme is a combination of classical control loops, a Kalman Estimator and analytical redundancy (for the airgap signal). In this way redundant airgap sensors are not essential for reliable operation of this system. When the airgap sensor fails the required signal is recovered using a combination of a Kalman estimator and analytical redundancy. The performance of the suspension is optimised using genetic algorithms and some preliminary robustness issues to load and operating airgap variations are discussed. Simulations on a realistic model of such type of suspension illustrate the efficacy of the proposed sensor tolerant control method.

Global root zone storage capacity from satellite-based evaporation data

NASA Astrophysics Data System (ADS)

Wang-Erlandsson, Lan; Bastiaanssen, Wim; Gao, Hongkai; Jägermeyr, Jonas; Senay, Gabriel; van Dijk, Albert; Guerschman, Juan; Keys, Patrick; Gordon, Line; Savenije, Hubert

2016-04-01

We present an "earth observation-based" method for estimating root zone storage capacity - a critical, yet uncertain parameter in hydrological and land surface modelling. By assuming that vegetation optimises its root zone storage capacity to bridge critical dry periods, we were able to use state-of-the-art satellite-based evaporation data computed with independent energy balance equations to derive gridded root zone storage capacity at global scale. This approach does not require soil or vegetation information, is model independent, and is in principle scale-independent. In contrast to traditional look-up table approaches, our method captures the variability in root zone storage capacity within land cover type, including in rainforests where direct measurements of root depth otherwise are scarce. Implementing the estimated root zone storage capacity in the global hydrological model STEAM improved evaporation simulation overall, and in particular during the least evaporating months in sub-humid to humid regions with moderate to high seasonality. We find that evergreen forests are able to create a large storage to buffer for extreme droughts (with a return period of up to 60 years), in contrast to short vegetation and crops (which seem to adapt to a drought return period of about 2 years). The presented method to estimate root zone storage capacity eliminates the need for soils and rooting depth information, which could be a game-changer in global land surface modelling.

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.

PubMed

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 trial is planned to determine the practicality of undertaking a definitive trial to robustly evaluate the effectiveness and cost-effectiveness of the optimised intervention on childhood obesity prevention. ClinicalTrials.gov identifier: NCT02675699 . Registered on 4 February 2016.

Observer roles that optimise learning in healthcare simulation education: a systematic review.

PubMed

O'Regan, Stephanie; Molloy, Elizabeth; Watterson, Leonie; Nestel, Debra

2016-01-01

Simulation is widely used in health professional education. The convention that learners are actively involved may limit access to this educational method. The aim of this paper is to review the evidence for learning methods that employ directed observation as an alternative to hands-on participation in scenario-based simulation training. We sought studies that included either direct comparison of the learning outcomes of observers with those of active participants or identified factors important for the engagement of observers in simulation. We systematically searched health and education databases and reviewed journals and bibliographies for studies investigating or referring to observer roles in simulation using mannequins, simulated patients or role play simulations. A quality framework was used to rate the studies. We sought studies that included either direct comparison of the learning outcomes of observers with those of active participants or identified factors important for the engagement of observers in simulation. We systematically searched health and education databases and reviewed journals and bibliographies for studies investigating or referring to observer roles in simulation using mannequins, simulated patients or role play simulations. A quality framework was used to rate the studies. Nine studies met the inclusion criteria. Five studies suggest learning outcomes in observer roles are as good or better than hands-on roles in simulation. Four studies document learner satisfaction in observer roles. Five studies used a tool to guide observers. Eight studies involved observers in the debrief. Learning and satisfaction in observer roles is closely associated with observer tools, learner engagement, role clarity and contribution to the debrief. Learners that valued observer roles described them as affording an overarching view, examination of details from a distance, and meaningful feedback during the debrief. Learners who did not value observer roles described them as passive, or boring when compared to hands-on engagement in the simulation encounter. Learning outcomes and role satisfaction for observers is improved through learner engagement and the use of observer tools. The value that students attach to observer roles appear contingent on role clarity, use of observer tools, and inclusion of observers' perspectives in the debrief.

Optimised analytical models of the dielectric properties of biological tissue.

PubMed

Salahuddin, Saqib; Porter, Emily; Krewer, Finn; O' Halloran, Martin

2017-05-01

The interaction of electromagnetic fields with the human body is quantified by the dielectric properties of biological tissues. These properties are incorporated into complex numerical simulations using parametric models such as Debye and Cole-Cole, for the computational investigation of electromagnetic wave propagation within the body. These parameters can be acquired through a variety of optimisation algorithms to achieve an accurate fit to measured data sets. A number of different optimisation techniques have been proposed, but these are often limited by the requirement for initial value estimations or by the large overall error (often up to several percentage points). In this work, a novel two-stage genetic algorithm proposed by the authors is applied to optimise the multi-pole Debye parameters for 54 types of human tissues. The performance of the two-stage genetic algorithm has been examined through a comparison with five other existing algorithms. The experimental results demonstrate that the two-stage genetic algorithm produces an accurate fit to a range of experimental data and efficiently out-performs all other optimisation algorithms under consideration. Accurate values of the three-pole Debye models for 54 types of human tissues, over 500 MHz to 20 GHz, are also presented for reference. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

A universal preconditioner for simulating condensed phase materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Packwood, David; Ortner, Christoph, E-mail: c.ortner@warwick.ac.uk; Kermode, James, E-mail: j.r.kermode@warwick.ac.uk

2016-04-28

We introduce a universal sparse preconditioner that accelerates geometry optimisation and saddle point search tasks that are common in the atomic scale simulation of materials. Our preconditioner is based on the neighbourhood structure and we demonstrate the gain in computational efficiency in a wide range of materials that include metals, insulators, and molecular solids. The simple structure of the preconditioner means that the gains can be realised in practice not only when using expensive electronic structure models but also for fast empirical potentials. Even for relatively small systems of a few hundred atoms, we observe speedups of a factor ofmore » two or more, and the gain grows with system size. An open source Python implementation within the Atomic Simulation Environment is available, offering interfaces to a wide range of atomistic codes.« less

Probabilistic Sizing and Verification of Space Ceramic Structures

NASA Astrophysics Data System (ADS)

Denaux, David; Ballhause, Dirk; Logut, Daniel; Lucarelli, Stefano; Coe, Graham; Laine, Benoit

2012-07-01

Sizing of ceramic parts is best optimised using a probabilistic approach which takes into account the preexisting flaw distribution in the ceramic part to compute a probability of failure of the part depending on the applied load, instead of a maximum allowable load as for a metallic part. This requires extensive knowledge of the material itself but also an accurate control of the manufacturing process. In the end, risk reduction approaches such as proof testing may be used to lower the final probability of failure of the part. Sizing and verification of ceramic space structures have been performed by Astrium for more than 15 years, both with Zerodur and SiC: Silex telescope structure, Seviri primary mirror, Herschel telescope, Formosat-2 instrument, and other ceramic structures flying today. Throughout this period of time, Astrium has investigated and developed experimental ceramic analysis tools based on the Weibull probabilistic approach. In the scope of the ESA/ESTEC study: “Mechanical Design and Verification Methodologies for Ceramic Structures”, which is to be concluded in the beginning of 2012, existing theories, technical state-of-the-art from international experts, and Astrium experience with probabilistic analysis tools have been synthesized into a comprehensive sizing and verification method for ceramics. Both classical deterministic and more optimised probabilistic methods are available, depending on the criticality of the item and on optimisation needs. The methodology, based on proven theory, has been successfully applied to demonstration cases and has shown its practical feasibility.

Optimising predictor domains for spatially coherent precipitation downscaling

NASA Astrophysics Data System (ADS)

Radanovics, S.; Vidal, J.-P.; Sauquet, E.; Ben Daoud, A.; Bontron, G.

2013-10-01

Statistical downscaling is widely used to overcome the scale gap between predictors from numerical weather prediction models or global circulation models and predictands like local precipitation, required for example for medium-term operational forecasts or climate change impact studies. The predictors are considered over a given spatial domain which is rarely optimised with respect to the target predictand location. In this study, an extended version of the growing rectangular domain algorithm is proposed to provide an ensemble of near-optimum predictor domains for a statistical downscaling method. This algorithm is applied to find five-member ensembles of near-optimum geopotential predictor domains for an analogue downscaling method for 608 individual target zones covering France. Results first show that very similar downscaling performances based on the continuous ranked probability score (CRPS) can be achieved by different predictor domains for any specific target zone, demonstrating the need for considering alternative domains in this context of high equifinality. A second result is the large diversity of optimised predictor domains over the country that questions the commonly made hypothesis of a common predictor domain for large areas. The domain centres are mainly distributed following the geographical location of the target location, but there are apparent differences between the windward and the lee side of mountain ridges. Moreover, domains for target zones located in southeastern France are centred more east and south than the ones for target locations on the same longitude. The size of the optimised domains tends to be larger in the southeastern part of the country, while domains with a very small meridional extent can be found in an east-west band around 47° N. Sensitivity experiments finally show that results are rather insensitive to the starting point of the optimisation algorithm except for zones located in the transition area north of this east-west band. Results also appear generally robust with respect to the archive length considered for the analogue method, except for zones with high interannual variability like in the Cévennes area. This study paves the way for defining regions with homogeneous geopotential predictor domains for precipitation downscaling over France, and therefore de facto ensuring the spatial coherence required for hydrological applications.

Statistical methods for convergence detection of multi-objective evolutionary algorithms.

PubMed

Trautmann, H; Wagner, T; Naujoks, B; Preuss, M; Mehnen, J

2009-01-01

In this paper, two approaches for estimating the generation in which a multi-objective evolutionary algorithm (MOEA) shows statistically significant signs of convergence are introduced. A set-based perspective is taken where convergence is measured by performance indicators. The proposed techniques fulfill the requirements of proper statistical assessment on the one hand and efficient optimisation for real-world problems on the other hand. The first approach accounts for the stochastic nature of the MOEA by repeating the optimisation runs for increasing generation numbers and analysing the performance indicators using statistical tools. This technique results in a very robust offline procedure. Moreover, an online convergence detection method is introduced as well. This method automatically stops the MOEA when either the variance of the performance indicators falls below a specified threshold or a stagnation of their overall trend is detected. Both methods are analysed and compared for two MOEA and on different classes of benchmark functions. It is shown that the methods successfully operate on all stated problems needing less function evaluations while preserving good approximation quality at the same time.

The robust model predictive control based on mixed H2/H∞ approach with separated performance formulations and its ISpS analysis

NASA Astrophysics Data System (ADS)

Li, Dewei; Li, Jiwei; Xi, Yugeng; Gao, Furong

2017-12-01

In practical applications, systems are always influenced by parameter uncertainties and external disturbance. Both the H2 performance and the H∞ performance are important for the real applications. For a constrained system, the previous designs of mixed H2/H∞ robust model predictive control (RMPC) optimise one performance with the other performance requirement as a constraint. But the two performances cannot be optimised at the same time. In this paper, an improved design of mixed H2/H∞ RMPC for polytopic uncertain systems with external disturbances is proposed to optimise them simultaneously. In the proposed design, the original uncertain system is decomposed into two subsystems by the additive character of linear systems. Two different Lyapunov functions are used to separately formulate the two performance indices for the two subsystems. Then, the proposed RMPC is designed to optimise both the two performances by the weighting method with the satisfaction of the H∞ performance requirement. Meanwhile, to make the design more practical, a simplified design is also developed. The recursive feasible conditions of the proposed RMPC are discussed and the closed-loop input state practical stable is proven. The numerical examples reflect the enlarged feasible region and the improved performance of the proposed design.

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

NASA Astrophysics Data System (ADS)

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 optimization problem (the best wells to retain in the monitoring network) depends on the total number of wells removed; this number is a management decision. The water level monitoring network of Mires basin has been optimized 6 times by removing 5, 8, 12, 15, 20 and 25 wells from the original network. In order to achieve the optimum solution in the minimum possible computational time, a stall generations criterion was set for each optimisation scenario. An improvement made to the classic genetic algorithm was the change of the mutation and crossover fraction in respect to the change of the mean fitness value. This results to a randomness in reproduction, if the solution converges, to avoid local minima, or, in a more educated reproduction (higher crossover ratio) when there is higher change in the mean fitness value. The choice of integer genetic algorithm in MATLAB 2015a poses the restriction of adding custom selection and crossover-mutation functions. Therefore, custom population and crossover-mutation-selection functions have been created to set the initial population type to custom and have the ability to change the mutation crossover probability in respect to the convergence of the genetic algorithm, achieving thus higher accuracy. The application of the network optimisation tool to Mires basin indicates that 25 wells can be removed with a relatively small deterioration of the groundwater level map. The results indicate the robustness of the network optimisation tool: Wells were removed from high well-density areas while preserving the spatial pattern of the original groundwater level map. Varouchakis, E. A. and D. T. Hristopulos (2013). "Improvement of groundwater level prediction in sparsely gauged basins using physical laws and local geographic features as auxiliary variables." Advances in Water Resources 52: 34-49.

Optimization of Phase Change Memory with Thin Metal Inserted Layer on Material Properties

NASA Astrophysics Data System (ADS)

Harnsoongnoen, Sanchai; Sa-Ngiamsak, Chiranut; Siritaratiwat, Apirat

This works reports, for the first time, the thorough study and optimisation of Phase Change Memory (PCM) structure with thin metal inserted chalcogenide via electrical resistivity (ρ) using finite element modeling. PCM is one of the best candidates for next generation non-volatile memory. It has received much attention recently due to its fast write speed, non-destructive readout, superb scalability, and great compatibility with current silicon-based mass fabrication. The setback of PCM is a high reset current typically higher than 1mA based on 180nm lithography. To reduce the reset current and to solve the over-programming failure, PCM with thin metal inserted chalcogenide (bottom chalcogenide/metal inserted/top chalcogenide) structure has been proposed. Nevertheless, reports on optimisation of the electrical resistivity using the finite element method for this new PCM structure have never been published. This work aims to minimize the reset current of this PCM structure by optimizing the level of the electrical resistivity of the PCM profile using the finite element approach. This work clearly shows that PCM characteristics are strongly affected by the electrical resistivity. The 2-D simulation results reveal clearly that the best thermal transfer of and self-joule-heating at the bottom chalcogenide layer can be achieved under conditions; ρ_bottom chalcogenide > ρ_metal inserted > ρ_top chalcogenide More specifically, the optimized electrical resistivity of PCMTMI is attained with ρ_top chalcogenide: ρ_metal inserted: ρ_bottom chalcogenide ratio of 1:6:16 when ρ_top chalcogenide is 10-3 Ωm. In conclusion, high energy efficiency can be obtained with the reset current as low as 0.3mA and with high speed operation of less than 30ns.

Cultural-based particle swarm for dynamic optimisation problems

NASA Astrophysics Data System (ADS)

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.

Design and simulation of a semiconductor chip-based visible - NIR spectrometer for Earth observation

NASA Astrophysics Data System (ADS)

Coote, J.; Woolliams, E.; Fox, N.; Goodyer, I. D.; Sweeney, S. J.

2014-03-01

We present the development of a novel semiconductor chip-based spectrometer for calibration of Earth observation instruments. The chip follows the Solo spectroscopy approach utilising an array of microdisk resonators evanescently coupled to a central waveguide. Each resonator is tuned to select out a specific wavelength from the incoming spectrum, and forms a p-i-n junction in which current is generated when light of the correct wavelength is present. In this paper we discuss important design aspects including the choice of semiconductor material, design of semiconductor quantum well structures for optical absorption, and design and optimisation of the waveguide and resonators.

IEEE 1982. Proceedings of the international conference on cybernetics and society

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1982-01-01

The following topics were dealt with: knowledge-based systems; risk analysis; man-machine interactions; human information processing; metaphor, analogy and problem-solving; manual control modelling; transportation systems; simulation; adaptive and learning systems; biocybernetics; cybernetics; mathematical programming; robotics; decision support systems; analysis, design and validation of models; computer vision; systems science; energy systems; environmental modelling and policy; pattern recognition; nuclear warfare; technological forecasting; artificial intelligence; the Turin shroud; optimisation; workloads. Abstracts of individual papers can be found under the relevant classification codes in this or future issues.

Circuit-level optimisation of a:Si TFT-based AMOLED pixel circuits for maximum hold current

NASA Astrophysics Data System (ADS)

Foroughi, Aidin; Mehrpoo, Mohammadreza; Ashtiani, Shahin J.

2013-11-01

Design of AMOLED pixel circuits has manifold constraints and trade-offs which provides incentive for circuit designers to seek optimal solutions for different objectives. In this article, we present a discussion on the viability of an optimal solution to achieve the maximum hold current. A compact formula for component sizing in a conventional 2T1C pixel is, therefore, derived. Compared to SPICE simulation results, for several pixel sizes, our predicted optimum sizing yields maximum currents with errors less than 0.4%.

3D printing process of oxidized nanocellulose and gelatin scaffold.

PubMed

Xu, Xiaodong; Zhou, Jiping; Jiang, Yani; Zhang, Qi; Shi, Hongcan; Liu, Dongfang

2018-08-01

For tissue engineering applications tissue scaffolds need to have a porous structure to meet the needs of cell proliferation/differentiation, vascularisation and sufficient mechanical strength for the specific tissue. Here we report the results of a study of the 3D printing process for composite materials based on oxidized nanocellulose and gelatin, that was optimised through measuring rheological properties of different batches of materials after different crosslinking times, simulation of the pneumatic extrusion process and 3D scaffolds fabrication with Solidworks Flow Simulation, observation of its porous structure by SEM, measurement of pressure-pull performance, and experiments aimed at finding out the vitro cytotoxicity and cell morphology. The materials printed are highly porous scaffolds with good mechanical properties.

Monitoring the enrichment of virgin olive oil with natural antioxidants by using a new capillary electrophoresis method.

PubMed

Nevado, Juan José Berzas; Robledo, Virginia Rodríguez; Callado, Carolina Sánchez-Carnerero

2012-07-15

The enrichment of virgin olive oil (VOO) with natural antioxidants contained in various herbs (rosemary, thyme and oregano) was studied. Three different enrichment procedures were used for the solid-liquid extraction of antioxidants present in the herbs to VOO. One involved simply bringing the herbs into contact with the VOO for 190 days; another keeping the herb-VOO mixture under stirring at room temperature (25°C) for 11 days; and the third stirring at temperatures above room level (35-40°C). The efficiency of each procedure was assessed by using a reproducible, efficient, reliable analytical capillary zone electrophoresis (CZE) method to separate and determine selected phenolic compounds (rosmarinic and caffeic acid) in the oil. Prior to electrophoretic separation, the studied antioxidants were isolated from the VOO matrix by using an optimised preconcentration procedure based on solid phase extraction (SPE). The CZE method was optimised and validated. Copyright © 2012 Elsevier Ltd. All rights reserved.

Very high frame rate volumetric integration of depth images on mobile devices.

PubMed

Kähler, Olaf; Adrian Prisacariu, Victor; Yuheng Ren, Carl; Sun, Xin; Torr, Philip; Murray, David

2015-11-01

Volumetric methods provide efficient, flexible and simple ways of integrating multiple depth images into a full 3D model. They provide dense and photorealistic 3D reconstructions, and parallelised implementations on GPUs achieve real-time performance on modern graphics hardware. To run such methods on mobile devices, providing users with freedom of movement and instantaneous reconstruction feedback, remains challenging however. In this paper we present a range of modifications to existing volumetric integration methods based on voxel block hashing, considerably improving their performance and making them applicable to tablet computer applications. We present (i) optimisations for the basic data structure, and its allocation and integration; (ii) a highly optimised raycasting pipeline; and (iii) extensions to the camera tracker to incorporate IMU data. In total, our system thus achieves frame rates up 47 Hz on a Nvidia Shield Tablet and 910 Hz on a Nvidia GTX Titan XGPU, or even beyond 1.1 kHz without visualisation.

A Bayesian Approach for Sensor Optimisation in Impact Identification

PubMed Central

Mallardo, Vincenzo; Sharif Khodaei, Zahra; Aliabadi, Ferri M. H.

2016-01-01

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. PMID:28774064

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

PubMed

Echtermeyer, Alexander; Amar, Yehia; Zakrzewski, Jacek; Lapkin, Alexei

2017-01-01

A recently described C(sp 3 )-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.

Generating a Dynamic Synthetic Population – Using an Age-Structured Two-Sex Model for Household Dynamics

PubMed Central

Namazi-Rad, Mohammad-Reza; Mokhtarian, Payam; Perez, Pascal

2014-01-01

Generating a reliable computer-simulated synthetic population is necessary for knowledge processing and decision-making analysis in agent-based systems in order to measure, interpret and describe each target area and the human activity patterns within it. In this paper, both synthetic reconstruction (SR) and combinatorial optimisation (CO) techniques are discussed for generating a reliable synthetic population for a certain geographic region (in Australia) using aggregated- and disaggregated-level information available for such an area. A CO algorithm using the quadratic function of population estimators is presented in this paper in order to generate a synthetic population while considering a two-fold nested structure for the individuals and households within the target areas. The baseline population in this study is generated from the confidentialised unit record files (CURFs) and 2006 Australian census tables. The dynamics of the created population is then projected over five years using a dynamic micro-simulation model for individual- and household-level demographic transitions. This projection is then compared with the 2011 Australian census. A prediction interval is provided for the population estimates obtained by the bootstrapping method, by which the variability structure of a predictor can be replicated in a bootstrap distribution. PMID:24733522

Optimisation of olive oil phenol extraction conditions using a high-power probe ultrasonication.

PubMed

Jerman Klen, T; Mozetič Vodopivec, B

2012-10-15

A new method of ultrasound probe assisted liquid-liquid extraction (US-LLE) combined with a freeze-based fat precipitation clean-up and HPLC-DAD-FLD-MS detection is described for extra virgin olive oil (EVOO) phenol analysis. Three extraction variables (solvent type; 100%, 80%, 50% methanol, sonication time; 5, 10, 20 min, extraction steps; 1-5) and two clean-up methods (n-hexane washing vs. low temperature fat precipitation) were studied and optimised with aim to maximise extracts' phenol recoveries. A three-step extraction of 10 min with pure methanol (5 mL) resulted in the highest phenol content of freeze-based defatted extracts (667 μg GAE g(-1)) from 10 g of EVOO, providing much higher efficiency (up to 68%) and repeatability (up to 51%) vs. its non-sonicated counterpart (LLE-agitation) and n-hexane washing. In addition, the overall method provided high linearity (r(2)≥0.97), precision (RSD: 0.4-9.3%) and sensitivity with LODs/LOQs ranging from 0.03 to 0.16 μg g(-1) and 0.10-0.51 μg g(-1) of EVOO, respectively. Copyright © 2012 Elsevier Ltd. All rights reserved.

Optimisation of insect cell growth in deep-well blocks: development of a high-throughput insect cell expression screen.

PubMed

Bahia, Daljit; Cheung, Robert; Buchs, Mirjam; Geisse, Sabine; Hunt, Ian

2005-01-01

This report describes a method to culture insects cells in 24 deep-well blocks for the routine small-scale optimisation of baculovirus-mediated protein expression experiments. Miniaturisation of this process provides the necessary reduction in terms of resource allocation, reagents, and labour to allow extensive and rapid optimisation of expression conditions, with the concomitant reduction in lead-time before commencement of large-scale bioreactor experiments. This therefore greatly simplifies the optimisation process and allows the use of liquid handling robotics in much of the initial optimisation stages of the process, thereby greatly increasing the throughput of the laboratory. We present several examples of the use of deep-well block expression studies in the optimisation of therapeutically relevant protein targets. We also discuss how the enhanced throughput offered by this approach can be adapted to robotic handling systems and the implications this has on the capacity to conduct multi-parallel protein expression studies.

Economic impact of optimising antiretroviral treatment in human immunodeficiency virus-infected adults with suppressed viral load in Spain, by implementing the grade A-1 evidence recommendations of the 2015 GESIDA/National AIDS Plan.

PubMed

Ribera, Esteban; Martínez-Sesmero, José Manuel; Sánchez-Rubio, Javier; Rubio, Rafael; Pasquau, Juan; Poveda, José Luis; Pérez-Mitru, Alejandro; Roldán, Celia; Hernández-Novoa, Beatriz

2018-03-01

The objective of this study is to estimate the economic impact associated with the optimisation of triple antiretroviral treatment (ART) in patients with undetectable viral load according to the recommendations from the GeSIDA/PNS (2015) Consensus and their applicability in the Spanish clinical practice. A pharmacoeconomic model was developed based on data from a National Hospital Prescription Survey on ART (2014) and the A-I evidence recommendations for the optimisation of ART from the GeSIDA/PNS (2015) consensus. The optimisation model took into account the willingness to optimise a particular regimen and other assumptions, and the results were validated by an expert panel in HIV infection (Infectious Disease Specialists and Hospital Pharmacists). The analysis was conducted from the NHS perspective, considering the annual wholesale price and accounting for deductions stated in the RD-Law 8/2010 and the VAT. The expert panel selected six optimisation strategies, and estimated that 10,863 (13.4%) of the 80,859 patients in Spain currently on triple ART, would be candidates to optimise their ART, leading to savings of €15.9M/year (2.4% of total triple ART drug cost). The most feasible strategies (>40% of patients candidates for optimisation, n=4,556) would be optimisations to ATV/r+3TC therapy. These would produce savings between €653 and €4,797 per patient per year depending on baseline triple ART. Implementation of the main optimisation strategies recommended in the GeSIDA/PNS (2015) Consensus into Spanish clinical practice would lead to considerable savings, especially those based in dual therapy with ATV/r+3TC, thus contributing to the control of pharmaceutical expenditure and NHS sustainability. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

A novel approach for the elimination of artefacts from EEG signals employing an improved Artificial Immune System algorithm

NASA Astrophysics Data System (ADS)

Suja Priyadharsini, S.; Edward Rajan, S.; Femilin Sheniha, S.

2016-03-01

Electroencephalogram (EEG) is the recording of electrical activities of the brain. It is contaminated by other biological signals, such as cardiac signal (electrocardiogram), signals generated by eye movement/eye blinks (electrooculogram) and muscular artefact signal (electromyogram), called artefacts. Optimisation is an important tool for solving many real-world problems. In the proposed work, artefact removal, based on the adaptive neuro-fuzzy inference system (ANFIS) is employed, by optimising the parameters of ANFIS. Artificial Immune System (AIS) algorithm is used to optimise the parameters of ANFIS (ANFIS-AIS). Implementation results depict that ANFIS-AIS is effective in removing artefacts from EEG signal than ANFIS. Furthermore, in the proposed work, improved AIS (IAIS) is developed by including suitable selection processes in the AIS algorithm. The performance of the proposed method IAIS is compared with AIS and with genetic algorithm (GA). Measures such as signal-to-noise ratio, mean square error (MSE) value, correlation coefficient, power spectrum density plot and convergence time are used for analysing the performance of the proposed method. From the results, it is found that the IAIS algorithm converges faster than the AIS and performs better than the AIS and GA. Hence, IAIS tuned ANFIS (ANFIS-IAIS) is effective in removing artefacts from EEG signals.

Characterization, optimisation and process robustness of a co-processed mannitol for the development of orally disintegrating tablets.

PubMed

Soh, Josephine Lay Peng; Grachet, Maud; Whitlock, Mark; Lukas, Timothy

2013-02-01

This is a study to fully assess a commercially available co-processed mannitol for its usefulness as an off-the-shelf excipient for developing orally disintegrating tablets (ODTs) by direct compression on a pilot scale (up to 4 kg). This work encompassed material characterization, formulation optimisation and process robustness. Overall, this co-processed mannitol possessed favourable physical attributes including low hygroscopicity and compactibility. Two design-of-experiments (DoEs) were used to screen and optimise the placebo formulation. Xylitol and crospovidone concentrations were found to have the most significant impact on disintegration time (p < 0.05). Higher xylitol concentrations retarded disintegration. Avicel PH102 promoted faster disintegration than PH101, at higher levels of xylitol. Without xylitol, higher crospovidone concentrations yielded faster disintegration and reduced tablet friability. Lubrication sensitivity studies were later conducted at two fill loads, three levels for lubricant concentration and number of blend rotations. Even at 75% fill load, the design space plot showed that 1.5% lubricant and 300 blend revolutions were sufficient to manufacture ODTs with ≤ 0.1% friability and disintegrated within 15 s. This study also describes results using a modified disintegration method based on the texture analyzer as an alternative to the USP method.

A brief understanding of process optimisation in microwave-assisted extraction of botanical materials: options and opportunities with chemometric tools.

PubMed

Das, Anup Kumar; Mandal, Vivekananda; Mandal, Subhash C

2014-01-01

Extraction forms the very basic step in research on natural products for drug discovery. A poorly optimised and planned extraction methodology can jeopardise the entire mission. To provide a vivid picture of different chemometric tools and planning for process optimisation and method development in extraction of botanical material, with emphasis on microwave-assisted extraction (MAE) of botanical material. A review of studies involving the application of chemometric tools in combination with MAE of botanical materials was undertaken in order to discover what the significant extraction factors were. Optimising a response by fine-tuning those factors, experimental design or statistical design of experiment (DoE), which is a core area of study in chemometrics, was then used for statistical analysis and interpretations. In this review a brief explanation of the different aspects and methodologies related to MAE of botanical materials that were subjected to experimental design, along with some general chemometric tools and the steps involved in the practice of MAE, are presented. A detailed study on various factors and responses involved in the optimisation is also presented. This article will assist in obtaining a better insight into the chemometric strategies of process optimisation and method development, which will in turn improve the decision-making process in selecting influential extraction parameters. Copyright © 2013 John Wiley & Sons, Ltd.

A joint technique for sidelobe suppression and peak-to-average power ratio reduction in non-contiguous OFDM-based cognitive radio networks

NASA Astrophysics Data System (ADS)

Sivadas, Namitha Arackal; Mohammed, Sameer Saheerudeen

2017-02-01

In non-contiguous orthogonal frequency division multiplexing (NC-OFDM)-based interweave cognitive radio networks, the sidelobe power of secondary users (SUs) must be strictly controlled to avoid the interference between the SUs and the primary users (PUs) of the adjacent bands. Similarly, the inherent issue of high peak-to-average power ratio (PAPR) of the OFDM signal is another drawback of the cognitive radio communication system based on the NC-OFDM technology. A few methods are available in the literature to solve either of these problems individually, while in this paper, we propose a new method for the joint minimisation of sidelobe power and PAPR in NC-OFDM-based cognitive radio networks using Zadoff-Chu (ZC) sequence. In this method, the sidelobe power suppression of SUs is benefited by PUs and the PAPR is reduced for SUs. We modelled a new optimisation problem for minimising the sidelobe power with a constraint on the maximum tolerable PAPR and sidelobe power. The proper selection of ZC sequence, which is crucial for minimising both the issues simultaneously, is achieved by solving the proposed optimisation problem. The proposed technique is shown to provide 7 dB and 20 dB reduction in PAPR and sidelobe power, respectively, without causing any signal distortion along with the improvement in bit error rate (BER) performance.

SENSOR: a tool for the simulation of hyperspectral remote sensing systems

NASA Astrophysics Data System (ADS)

Börner, Anko; Wiest, Lorenz; Keller, Peter; Reulke, Ralf; Richter, Rolf; Schaepman, Michael; Schläpfer, Daniel

The consistent end-to-end simulation of airborne and spaceborne earth remote sensing systems is an important task, and sometimes the only way for the adaptation and optimisation of a sensor and its observation conditions, the choice and test of algorithms for data processing, error estimation and the evaluation of the capabilities of the whole sensor system. The presented software simulator SENSOR (Software Environment for the Simulation of Optical Remote sensing systems) includes a full model of the sensor hardware, the observed scene, and the atmosphere in between. The simulator consists of three parts. The first part describes the geometrical relations between scene, sun, and the remote sensing system using a ray-tracing algorithm. The second part of the simulation environment considers the radiometry. It calculates the at-sensor radiance using a pre-calculated multidimensional lookup-table taking the atmospheric influence on the radiation into account. The third part consists of an optical and an electronic sensor model for the generation of digital images. Using SENSOR for an optimisation requires the additional application of task-specific data processing algorithms. The principle of the end-to-end-simulation approach is explained, all relevant concepts of SENSOR are discussed, and first examples of its use are given. The verification of SENSOR is demonstrated. This work is closely related to the Airborne PRISM Experiment (APEX), an airborne imaging spectrometer funded by the European Space Agency.

PGA/MOEAD: a preference-guided evolutionary algorithm for multi-objective decision-making problems with interval-valued fuzzy preferences

NASA Astrophysics Data System (ADS)

Luo, Bin; Lin, Lin; Zhong, ShiSheng

2018-02-01

In this research, we propose a preference-guided optimisation algorithm for multi-criteria decision-making (MCDM) problems with interval-valued fuzzy preferences. The interval-valued fuzzy preferences are decomposed into a series of precise and evenly distributed preference-vectors (reference directions) regarding the objectives to be optimised on the basis of uniform design strategy firstly. Then the preference information is further incorporated into the preference-vectors based on the boundary intersection approach, meanwhile, the MCDM problem with interval-valued fuzzy preferences is reformulated into a series of single-objective optimisation sub-problems (each sub-problem corresponds to a decomposed preference-vector). Finally, a preference-guided optimisation algorithm based on MOEA/D (multi-objective evolutionary algorithm based on decomposition) is proposed to solve the sub-problems in a single run. The proposed algorithm incorporates the preference-vectors within the optimisation process for guiding the search procedure towards a more promising subset of the efficient solutions matching the interval-valued fuzzy preferences. In particular, lots of test instances and an engineering application are employed to validate the performance of the proposed algorithm, and the results demonstrate the effectiveness and feasibility of the algorithm.

Nonconvex model predictive control for commercial refrigeration

NASA Astrophysics Data System (ADS)

Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John

2013-08-01

We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.

The implementation of microstructural and heat treatment models to development of forming technology of critical aluminum-alloy parts

NASA Astrophysics Data System (ADS)

Biba, Nikolay; Alimov, Artem; Shitikov, Andrey; Stebunov, Sergei

2018-05-01

The demand for high performance and energy efficient transportation systems have boosted interest in lightweight design solutions. To achieve maximum weight reductions, it is not enough just to replace steel parts by their aluminium analogues, but it is necessary to change the entire concept of vehicle design. In this case we must develop methods for manufacturing a variety of critical parts with unusual and difficult to produce shapes. The mechanical properties of the material in these parts must also be optimised and tightly controlled to provide the best distribution within the part volume. The only way to achieve these goals is to implement technology development methods based on simulation of the entire manufacturing chain from preparing a billet through the forming operations and heat treatment of the product. The paper presents an approach to such technology development. The simulation of the technological chain starts with extruding a round billet. Depending on the extrusion process parameters, the billet can have different levels of material workout and variation of grain size throughout the volume. After extrusion, the billet gets formed into the required shape in a forging process. The main requirements at this stage are to get the near net shape of the product without defects and to provide proper configuration of grain flow that strengthens the product in the most critical direction. Then the product undergoes solution treatment, quenching and ageing. The simulation of all these stages are performed by QForm FEM code that provides thermo-mechanical coupled deformation of the material during extrusion and forging. To provide microstructure and heat treatment simulation, special subroutines has been developed by the authors. The proposed approach is illustrated by an industrial case study.

AC loss modelling and experiment of two types of low-inductance solenoidal coils

NASA Astrophysics Data System (ADS)

Liang, Fei; Yuan, Weijia; Zhang, Min; Zhang, Zhenyu; Li, Jianwei; Venuturumilli, Sriharsha; Patel, Jay

2016-11-01

Low-inductance solenoidal coils, which usually refer to the nonintersecting type and the braid type, have already been employed to build superconducting fault current limiters because of their fast recovery and low inductance characteristics. However, despite their usage there is still no systematical simulation work concerning the AC loss characteristics of the coils built with 2G high temperature superconducting tapes perhaps because of their complicated structure. In this paper, a new method is proposed to simulate both types of coils with 2D axisymmetric models solved by H formulation. Following the simulation work, AC losses of both types of low inductance solenoidal coils are compared numerically and experimentally, which verify that the model works well in simulating non-inductive coils. Finally, simulation works show that pitch has significant impact to AC loss of both types of coils and the inter-layer separation has different impact to the AC loss of braid type of coil in case of different applied currents. The model provides an effective tool for the design optimisation of SFCLs built with non-inductive solenoidal coils.

Risk management algorithm for rear-side collision avoidance using a combined steering torque overlay and differential braking

NASA Astrophysics Data System (ADS)

Lee, Junyung; Yi, Kyongsu; Yoo, Hyunjae; Chong, Hyokjin; Ko, Bongchul

2015-06-01

This paper describes a risk management algorithm for rear-side collision avoidance. The proposed risk management algorithm consists of a supervisor and a coordinator. The supervisor is designed to monitor collision risks between the subject vehicle and approaching vehicle in the adjacent lane. An appropriate criterion of intervention, which satisfies high acceptance to drivers through the consideration of a realistic traffic, has been determined based on the analysis of the kinematics of the vehicles in longitudinal and lateral directions. In order to assist the driver actively and increase driver's safety, a coordinator is designed to combine lateral control using a steering torque overlay by motor-driven power steering and differential braking by vehicle stability control. In order to prevent the collision while limiting actuator's control inputs and vehicle dynamics to safe values for the assurance of the driver's comfort, the Lyapunov theory and linear matrix inequalities based optimisation methods have been used. The proposed risk management algorithm has been evaluated via simulation using CarSim and MATLAB/Simulink.

Global Topology Optimisation

DTIC Science & Technology

2016-10-31

statistical physics. Sec. IV includes several examples of the application of the stochastic method, including matching of a shape to a fixed design, and...an important part of any future application of this method. Second, re-initialization of the level set can lead to small but significant movements of...of engineering design problems [6, 17]. However, many of the relevant applications involve non-convex optimisation problems with multiple locally

Wind energy resource modelling in Portugal and its future large-scale alteration due to anthropogenic induced climate changes =

NASA Astrophysics Data System (ADS)

Carvalho, David Joao da Silva

The high dependence of Portugal from foreign energy sources (mainly fossil fuels), together with the international commitments assumed by Portugal and the national strategy in terms of energy policy, as well as resources sustainability and climate change issues, inevitably force Portugal to invest in its energetic self-sufficiency. The 20/20/20 Strategy defined by the European Union defines that in 2020 60% of the total electricity consumption must come from renewable energy sources. Wind energy is currently a major source of electricity generation in Portugal, producing about 23% of the national total electricity consumption in 2013. The National Energy Strategy 2020 (ENE2020), which aims to ensure the national compliance of the European Strategy 20/20/20, states that about half of this 60% target will be provided by wind energy. This work aims to implement and optimise a numerical weather prediction model in the simulation and modelling of the wind energy resource in Portugal, both in offshore and onshore areas. The numerical model optimisation consisted in the determination of which initial and boundary conditions and planetary boundary layer physical parameterizations options provide wind power flux (or energy density), wind speed and direction simulations closest to in situ measured wind data. Specifically for offshore areas, it is also intended to evaluate if the numerical model, once optimised, is able to produce power flux, wind speed and direction simulations more consistent with in situ measured data than wind measurements collected by satellites. This work also aims to study and analyse possible impacts that anthropogenic climate changes may have on the future wind energetic resource in Europe. The results show that the ECMWF reanalysis ERA-Interim are those that, among all the forcing databases currently available to drive numerical weather prediction models, allow wind power flux, wind speed and direction simulations more consistent with in situ wind measurements. It was also found that the Pleim-Xiu and ACM2 planetary boundary layer parameterizations are the ones that showed the best performance in terms of wind power flux, wind speed and direction simulations. This model optimisation allowed a significant reduction of the wind power flux, wind speed and direction simulations errors and, specifically for offshore areas, wind power flux, wind speed and direction simulations more consistent with in situ wind measurements than data obtained from satellites, which is a very valuable and interesting achievement. This work also revealed that future anthropogenic climate changes can negatively impact future European wind energy resource, due to tendencies towards a reduction in future wind speeds especially by the end of the current century and under stronger radiative forcing conditions.

Transformer ratio saturation in a beam-driven wakefield accelerator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farmer, J. P.; Martorelli, R.; Pukhov, A.

We show that for beam-driven wakefield acceleration, the linearly ramped, equally spaced train of bunches typically considered to optimise the transformer ratio only works for flat-top bunches. Through theory and simulation, we explain that this behaviour is due to the unique properties of the plasma response to a flat-top density profile. Calculations of the optimal scaling for a train of Gaussian bunches show diminishing returns with increasing bunch number, tending towards saturation. For a periodic bunch train, a transformer ratio of 23 was achieved for 50 bunches, rising to 40 for a fully optimised beam.

Monte carlo study of MOSFET packaging, optimised for improved energy response: single MOSFET filtration.

PubMed

Othman, M A R; Cutajar, D L; Hardcastle, N; Guatelli, S; Rosenfeld, A B

2010-09-01

Monte Carlo simulations of the energy response of a conventionally packaged single metal-oxide field effect transistors (MOSFET) detector were performed with the goal of improving MOSFET energy dependence for personal accident or military dosimetry. The MOSFET detector packaging was optimised. Two different 'drop-in' design packages for a single MOSFET detector were modelled and optimised using the GEANT4 Monte Carlo toolkit. Absorbed photon dose simulations of the MOSFET dosemeter placed in free-air response, corresponding to the absorbed doses at depths of 0.07 mm (D(w)(0.07)) and 10 mm (D(w)(10)) in a water equivalent phantom of size 30 x 30 x 30 cm(3) for photon energies of 0.015-2 MeV were performed. Energy dependence was reduced to within + or - 60 % for photon energies 0.06-2 MeV for both D(w)(0.07) and D(w)(10). Variations in the response for photon energies of 15-60 keV were 200 and 330 % for D(w)(0.07) and D(w)(10), respectively. The obtained energy dependence was reduced compared with that for conventionally packaged MOSFET detectors, which usually exhibit a 500-700 % over-response when used in free-air geometry.

Miniature microwave applicator for murine bladder hyperthermia studies.

PubMed

Salahi, Sara; Maccarini, Paolo F; Rodrigues, Dario B; Etienne, Wiguins; Landon, Chelsea D; Inman, Brant A; Dewhirst, Mark W; Stauffer, Paul R

2012-01-01

Novel combinations of heat with chemotherapeutic agents are often studied in murine tumour models. Currently, no device exists to selectively heat small tumours at depth in mice. In this project we modelled, built and tested a miniature microwave heat applicator, the physical dimensions of which can be scaled to adjust the volume and depth of heating to focus on the tumour volume. Of particular interest is a device that can selectively heat murine bladder. Using Avizo(®) segmentation software, we created a numerical mouse model based on micro-MRI scan data. The model was imported into HFSS™ (Ansys) simulation software and parametric studies were performed to optimise the dimensions of a water-loaded circular waveguide for selective power deposition inside a 0.15 mL bladder. A working prototype was constructed operating at 2.45 GHz. Heating performance was characterised by mapping fibre-optic temperature sensors along catheters inserted at depths of 0-1 mm (subcutaneous), 2-3 mm (vaginal), and 4-5 mm (rectal) below the abdominal wall, with the mid depth catheter adjacent to the bladder. Core temperature was monitored orally. Thermal measurements confirm the simulations which demonstrate that this applicator can provide local heating at depth in small animals. Measured temperatures in murine pelvis show well-localised bladder heating to 42-43°C while maintaining normothermic skin and core temperatures. Simulation techniques facilitate the design optimisation of microwave antennas for use in pre-clinical applications such as localised tumour heating in small animals. Laboratory measurements demonstrate the effectiveness of a new miniature water-coupled microwave applicator for localised heating of murine bladder.

Understanding ageing in older Australians: The contribution of the Dynamic Analyses to Optimise Ageing (DYNOPTA) project to the evidenced base and policy

PubMed Central

Anstey, Kaarin J; Bielak, Allison AM; Birrell, Carole L; Browning, Colette J; Burns, Richard A; Byles, Julie; Kiley, Kim M; Nepal, Binod; Ross, Lesley A; Steel, David; Windsor, Timothy D

2014-01-01

Aim To describe the Dynamic Analyses to Optimise Ageing (DYNOPTA) project and illustrate its contributions to understanding ageing through innovative methodology, and investigations on outcomes based on the project themes. DYNOPTA provides a platform and technical expertise that may be used to combine other national and international datasets. Method The DYNOPTA project has pooled and harmonized data from nine Australian longitudinal studies to create the largest available longitudinal dataset (N=50652) on ageing in Australia. Results A range of findings have resulted from the study to date, including methodological advances, prevalence rates of disease and disability, and mapping trajectories of ageing with and without increasing morbidity. DYNOPTA also forms the basis of a microsimulation model that will provide projections of future costs of disease and disability for the baby boomer cohort. Conclusion DYNOPTA contributes significantly to the Australian evidence-base on ageing to inform key social and health policy domains. PMID:22032767

Optimisation of SOA-REAMs for hybrid DWDM-TDMA PON applications.

PubMed

Naughton, Alan; Antony, Cleitus; Ossieur, Peter; Porto, Stefano; Talli, Giuseppe; Townsend, Paul D

2011-12-12

We demonstrate how loss-optimised, gain-saturated SOA-REAM based reflective modulators can reduce the burst to burst power variations due to differential access loss in the upstream path in carrier distributed passive optical networks by 18 dB compared to fixed linear gain modulators. We also show that the loss optimised device has a high tolerance to input power variations and can operate in deep saturation with minimal patterning penalties. Finally, we demonstrate that an optimised device can operate across the C-Band and also over a transmission distance of 80 km. © 2011 Optical Society of America

On the Performance of Alternate Conceptual Ecohydrological Models for Streamflow Prediction

NASA Astrophysics Data System (ADS)

Naseem, Bushra; Ajami, Hoori; Cordery, Ian; Sharma, Ashish

2016-04-01

A merging of a lumped conceptual hydrological model with two conceptual dynamic vegetation models is presented to assess the performance of these models for simultaneous simulations of streamflow and leaf area index (LAI). Two conceptual dynamic vegetation models with differing representation of ecological processes are merged with a lumped conceptual hydrological model (HYMOD) to predict catchment scale streamflow and LAI. The merged RR-LAI-I model computes relative leaf biomass based on transpiration rates while the RR-LAI-II model computes above ground green and dead biomass based on net primary productivity and water use efficiency in response to soil moisture dynamics. To assess the performance of these models, daily discharge and 8-day MODIS LAI product for 27 catchments of 90 - 1600km2 in size located in the Murray - Darling Basin in Australia are used. Our results illustrate that when single-objective optimisation was focussed on maximizing the objective function for streamflow or LAI, the other un-calibrated predicted outcome (LAI if streamflow is the focus) was consistently compromised. Thus, single-objective optimization cannot take into account the essence of all processes in the conceptual ecohydrological models. However, multi-objective optimisation showed great strength for streamflow and LAI predictions. Both response outputs were better simulated by RR-LAI-II than RR-LAI-I due to better representation of physical processes such as net primary productivity (NPP) in RR-LAI-II. Our results highlight that simultaneous calibration of streamflow and LAI using a multi-objective algorithm proves to be an attractive tool for improved streamflow predictions.

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

PubMed

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.

Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

NASA Astrophysics Data System (ADS)

Demirel, Mehmet C.; Mai, Juliane; Mendiguren, Gorka; Koch, Julian; Samaniego, Luis; Stisen, Simon

2018-02-01

Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex evolution optimiser. The calibration results reveal a limited trade-off between streamflow dynamics and spatial patterns illustrating the benefit of combining separate observation types and objective functions. At the same time, the simulated spatial patterns of AET significantly improved when an objective function based on observed AET patterns and a novel spatial performance metric compared to traditional streamflow-only calibration were included. Since the overall water balance is usually a crucial goal in hydrologic modelling, spatial-pattern-oriented optimisation should always be accompanied by traditional discharge measurements. In such a multi-objective framework, the current study promotes the use of a novel bias-insensitive spatial pattern metric, which exploits the key information contained in the observed patterns while allowing the water balance to be informed by discharge observations.

Shape Optimisation of Holes in Loaded Plates by Minimisation of Multiple Stress Peaks

DTIC Science & Technology

2015-04-01

UNCLASSIFIED UNCLASSIFIED Shape Optimisation of Holes in Loaded Plates by Minimisation of Multiple Stress Peaks Witold Waldman and Manfred...minimising the peak tangential stresses on multiple segments around the boundary of a hole in a uniaxially-loaded or biaxially-loaded plate . It is based...RELEASE UNCLASSIFIED UNCLASSIFIED Shape Optimisation of Holes in Loaded Plates by Minimisation of Multiple Stress Peaks Executive Summary Aerospace

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

PubMed

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.

Escalated convergent artificial bee colony

NASA Astrophysics Data System (ADS)

Jadon, Shimpi Singh; Bansal, Jagdish Chand; Tiwari, Ritu

2016-03-01

Artificial bee colony (ABC) optimisation algorithm is a recent, fast and easy-to-implement population-based meta heuristic for optimisation. ABC has been proved a rival algorithm with some popular swarm intelligence-based algorithms such as particle swarm optimisation, firefly algorithm and ant colony optimisation. The solution search equation of ABC is influenced by a random quantity which helps its search process in exploration at the cost of exploitation. In order to find a fast convergent behaviour of ABC while exploitation capability is maintained, in this paper basic ABC is modified in two ways. First, to improve exploitation capability, two local search strategies, namely classical unidimensional local search and levy flight random walk-based local search are incorporated with ABC. Furthermore, a new solution search strategy, namely stochastic diffusion scout search is proposed and incorporated into the scout bee phase to provide more chance to abandon solution to improve itself. Efficiency of the proposed algorithm is tested on 20 benchmark test functions of different complexities and characteristics. Results are very promising and they prove it to be a competitive algorithm in the field of swarm intelligence-based algorithms.

Evaluation and optimisation of phenomenological multi-step soot model for spray combustion under diesel engine-like operating conditions

NASA Astrophysics Data System (ADS)

Pang, Kar Mun; Jangi, Mehdi; Bai, Xue-Song; Schramm, Jesper

2015-05-01

In this work, a two-dimensional computational fluid dynamics study is reported of an n-heptane combustion event and the associated soot formation process in a constant volume combustion chamber. The key interest here is to evaluate the sensitivity of the chemical kinetics and submodels of a semi-empirical soot model in predicting the associated events. Numerical computation is performed using an open-source code and a chemistry coordinate mapping approach is used to expedite the calculation. A library consisting of various phenomenological multi-step soot models is constructed and integrated with the spray combustion solver. Prior to the soot modelling, combustion simulations are carried out. Numerical results show that the ignition delay times and lift-off lengths exhibit good agreement with the experimental measurements across a wide range of operating conditions, apart from those in the cases with ambient temperature lower than 850 K. The variation of the soot precursor production with respect to the change of ambient oxygen levels qualitatively agrees with that of the conceptual models when the skeletal n-heptane mechanism is integrated with a reduced pyrene chemistry. Subsequently, a comprehensive sensitivity analysis is carried out to appraise the existing soot formation and oxidation submodels. It is revealed that the soot formation is captured when the surface growth rate is calculated using a square root function of the soot specific surface area and when a pressure-dependent model constant is considered. An optimised soot model is then proposed based on the knowledge gained through this exercise. With the implementation of optimised model, the simulated soot onset and transport phenomena before reaching quasi-steady state agree reasonably well with the experimental observation. Also, variation of spatial soot distribution and soot mass produced at oxygen molar fractions ranging from 10.0 to 21.0% for both low and high density conditions are reproduced.

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

PubMed Central

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

2012-01-01

Purpose: 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. Materials and Methods: 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 23 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. Results: 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. Conclusion: 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. PMID:23580933

Auto-calibration of a one-dimensional hydrodynamic-ecological model using a Monte Carlo approach: simulation of hypoxic events in a polymictic lake

NASA Astrophysics Data System (ADS)

Luo, L.

2011-12-01

Automated calibration of complex deterministic water quality models with a large number of biogeochemical parameters can reduce time-consuming iterative simulations involving empirical judgements of model fit. We undertook auto-calibration of the one-dimensional hydrodynamic-ecological lake model DYRESM-CAEDYM, using a Monte Carlo sampling (MCS) method, in order to test the applicability of this procedure for shallow, polymictic Lake Rotorua (New Zealand). The calibration procedure involved independently minimising the root-mean-square-error (RMSE), maximizing the Pearson correlation coefficient (r) and Nash-Sutcliffe efficient coefficient (Nr) for comparisons of model state variables against measured data. An assigned number of parameter permutations was used for 10,000 simulation iterations. The 'optimal' temperature calibration produced a RMSE of 0.54 °C, Nr-value of 0.99 and r-value of 0.98 through the whole water column based on comparisons with 540 observed water temperatures collected between 13 July 2007 - 13 January 2009. The modeled bottom dissolved oxygen concentration (20.5 m below surface) was compared with 467 available observations. The calculated RMSE of the simulations compared with the measurements was 1.78 mg L-1, the Nr-value was 0.75 and the r-value was 0.87. The autocalibrated model was further tested for an independent data set by simulating bottom-water hypoxia events for the period 15 January 2009 to 8 June 2011 (875 days). This verification produced an accurate simulation of five hypoxic events corresponding to DO < 2 mg L-1 during summer of 2009-2011. The RMSE was 2.07 mg L-1, Nr-value 0.62 and r-value of 0.81, based on the available data set of 738 days. The auto-calibration software of DYRESM-CAEDYM developed here is substantially less time-consuming and more efficient in parameter optimisation than traditional manual calibration which has been the standard tool practiced for similar complex water quality models.

Finite element analysis of the design and manufacture of thin-walled pressure vessels used as aerosol cans

NASA Astrophysics Data System (ADS)

Abdussalam, Ragba Mohamed

Thin-walled cylinders are used extensively in the food packaging and cosmetics industries. The cost of material is a major contributor to the overall cost and so improvements in design and manufacturing processes are always being sought. Shape optimisation provides one method for such improvements. Aluminium aerosol cans are a particular form of thin-walled cylinder with a complex shape consisting of truncated cone top, parallel cylindrical section and inverted dome base. They are manufactured in one piece by a reverse-extrusion process, which produces a vessel with a variable thickness from 0.31 mm in the cylinder up to 1.31 mm in the base for a 53 mm diameter can. During manufacture, packaging and charging, they are subjected to pressure, axial and radial loads and design calculations are generally outside the British and American pressure vessel codes. 'Design-by-test' appears to be the favoured approach. However, a more rigorous approach is needed in order to optimise the designs. Finite element analysis (FEA) is a powerful tool for predicting stress, strain and displacement behaviour of components and structures. FEA is also used extensively to model manufacturing processes. In this study, elastic and elastic-plastic FEA has been used to develop a thorough understanding of the mechanisms of yielding, 'dome reversal' (an inherent safety feature, where the base suffers elastic-plastic buckling at a pressure below the burst pressure) and collapse due to internal pressure loading and how these are affected by geometry. It has also been used to study the buckling behaviour under compressive axial loading. Furthermore, numerical simulations of the extrusion process (in order to investigate the effects of tool geometry, friction coefficient and boundary conditions) have been undertaken. Experimental verification of the buckling and collapse behaviours has also been carried out and there is reasonable agreement between the experimental data and the numerical predictions.

Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework.

PubMed

Yang, Lingjian; Ainali, Chrysanthi; Tsoka, Sophia; Papageorgiou, Lazaros G

2014-12-05

Applying machine learning methods on microarray gene expression profiles for disease classification problems is a popular method to derive biomarkers, i.e. sets of genes that can predict disease state or outcome. Traditional approaches where expression of genes were treated independently suffer from low prediction accuracy and difficulty of biological interpretation. Current research efforts focus on integrating information on protein interactions through biochemical pathway datasets with expression profiles to propose pathway-based classifiers that can enhance disease diagnosis and prognosis. As most of the pathway activity inference methods in literature are either unsupervised or applied on two-class datasets, there is good scope to address such limitations by proposing novel methodologies. A supervised multiclass pathway activity inference method using optimisation techniques is reported. For each pathway expression dataset, patterns of its constituent genes are summarised into one composite feature, termed pathway activity, and a novel mathematical programming model is proposed to infer this feature as a weighted linear summation of expression of its constituent genes. Gene weights are determined by the optimisation model, in a way that the resulting pathway activity has the optimal discriminative power with regards to disease phenotypes. Classification is then performed on the resulting low-dimensional pathway activity profile. The model was evaluated through a variety of published gene expression profiles that cover different types of disease. We show that not only does it improve classification accuracy, but it can also perform well in multiclass disease datasets, a limitation of other approaches from the literature. Desirable features of the model include the ability to control the maximum number of genes that may participate in determining pathway activity, which may be pre-specified by the user. Overall, this work highlights the potential of building pathway-based multi-phenotype classifiers for accurate disease diagnosis and prognosis problems.

Review of Modelling Techniques for In Vivo Muscle Force Estimation in the Lower Extremities during Strength Training

PubMed Central

Schellenberg, Florian; Oberhofer, Katja; Taylor, William R.

2015-01-01

Background. Knowledge of the musculoskeletal loading conditions during strength training is essential for performance monitoring, injury prevention, rehabilitation, and training design. However, measuring muscle forces during exercise performance as a primary determinant of training efficacy and safety has remained challenging. Methods. In this paper we review existing computational techniques to determine muscle forces in the lower limbs during strength exercises in vivo and discuss their potential for uptake into sports training and rehabilitation. Results. Muscle forces during exercise performance have almost exclusively been analysed using so-called forward dynamics simulations, inverse dynamics techniques, or alternative methods. Musculoskeletal models based on forward dynamics analyses have led to considerable new insights into muscular coordination, strength, and power during dynamic ballistic movement activities, resulting in, for example, improved techniques for optimal performance of the squat jump, while quasi-static inverse dynamics optimisation and EMG-driven modelling have helped to provide an understanding of low-speed exercises. Conclusion. The present review introduces the different computational techniques and outlines their advantages and disadvantages for the informed usage by nonexperts. With sufficient validation and widespread application, muscle force calculations during strength exercises in vivo are expected to provide biomechanically based evidence for clinicians and therapists to evaluate and improve training guidelines. PMID:26417378

Performance analysis of cross-layer design with average PER constraint over MIMO fading channels

NASA Astrophysics Data System (ADS)

Dang, Xiaoyu; Liu, Yan; Yu, Xiangbin

2015-12-01

In this article, a cross-layer design (CLD) scheme for multiple-input and multiple-output system with the dual constraints of imperfect feedback and average packet error rate (PER) is presented, which is based on the combination of the adaptive modulation and the automatic repeat request protocols. The design performance is also evaluated over wireless Rayleigh fading channel. With the constraint of target PER and average PER, the optimum switching thresholds (STs) for attaining maximum spectral efficiency (SE) are developed. An effective iterative algorithm for finding the optimal STs is proposed via Lagrange multiplier optimisation. With different thresholds available, the analytical expressions of the average SE and PER are provided for the performance evaluation. To avoid the performance loss caused by the conventional single estimate, multiple outdated estimates (MOE) method, which utilises multiple previous channel estimation information, is presented for CLD to improve the system performance. It is shown that numerical simulations for average PER and SE are in consistent with the theoretical analysis and that the developed CLD with average PER constraint can meet the target PER requirement and show better performance in comparison with the conventional CLD with instantaneous PER constraint. Especially, the CLD based on the MOE method can obviously increase the system SE and reduce the impact of feedback delay greatly.

redNumerical modelling of a peripheral arterial stenosis using dimensionally reduced models and kernel methods.

PubMed

Köppl, Tobias; Santin, Gabriele; Haasdonk, Bernard; Helmig, Rainer

2018-05-06

In this work, we consider two kinds of model reduction techniques to simulate blood flow through the largest systemic arteries, where a stenosis is located in a peripheral artery i.e. in an artery that is located far away from the heart. For our simulations we place the stenosis in one of the tibial arteries belonging to the right lower leg (right post tibial artery). The model reduction techniques that are used are on the one hand dimensionally reduced models (1-D and 0-D models, the so-called mixed-dimension model) and on the other hand surrogate models produced by kernel methods. Both methods are combined in such a way that the mixed-dimension models yield training data for the surrogate model, where the surrogate model is parametrised by the degree of narrowing of the peripheral stenosis. By means of a well-trained surrogate model, we show that simulation data can be reproduced with a satisfactory accuracy and that parameter optimisation or state estimation problems can be solved in a very efficient way. Furthermore it is demonstrated that a surrogate model enables us to present after a very short simulation time the impact of a varying degree of stenosis on blood flow, obtaining a speedup of several orders over the full model. This article is protected by copyright. All rights reserved.

An automated method for the analysis of phenolic acids in plasma based on ion-pairing micro-extraction coupled on-line to gas chromatography/mass spectrometry with in-liner derivatisation.

PubMed

Peters, Sonja; Kaal, Erwin; Horsting, Iwan; Janssen, Hans-Gerd

2012-02-24

A new method is presented for the analysis of phenolic acids in plasma based on ion-pairing 'Micro-extraction in packed sorbent' (MEPS) coupled on-line to in-liner derivatisation-gas chromatography-mass spectrometry (GC-MS). The ion-pairing reagent served a dual purpose. It was used both to improve extraction yields of the more polar analytes and as the methyl donor in the automated in-liner derivatisation method. In this way, a fully automated procedure for the extraction, derivatisation and injection of a wide range of phenolic acids in plasma samples has been obtained. An extensive optimisation of the extraction and derivatisation procedure has been performed. The entire method showed excellent repeatabilities of under 10% and linearities of 0.99 or better for all phenolic acids. The limits of detection of the optimised method for the majority of phenolic acids were 10ng/mL or lower with three phenolic acids having less-favourable detection limits of around 100 ng/mL. Finally, the newly developed method has been applied in a human intervention trial in which the bioavailability of polyphenols from wine and tea was studied. Forty plasma samples could be analysed within 24h in a fully automated method including sample extraction, derivatisation and gas chromatographic analysis. Copyright © 2011 Elsevier B.V. All rights reserved.

Explicit reference governor for linear systems

NASA Astrophysics Data System (ADS)

Garone, Emanuele; Nicotra, Marco; Ntogramatzidis, Lorenzo

2018-06-01

The explicit reference governor is a constrained control scheme that was originally introduced for generic nonlinear systems. This paper presents two explicit reference governor strategies that are specifically tailored for the constrained control of linear time-invariant systems subject to linear constraints. Both strategies are based on the idea of maintaining the system states within an invariant set which is entirely contained in the constraints. This invariant set can be constructed by exploiting either the Lyapunov inequality or modal decomposition. To improve the performance, we show that the two strategies can be combined by choosing at each time instant the least restrictive set. Numerical simulations illustrate that the proposed scheme achieves performances that are comparable to optimisation-based reference governors.

Global root zone storage capacity from satellite-based evaporation

NASA Astrophysics Data System (ADS)

Wang-Erlandsson, Lan; Bastiaanssen, Wim G. M.; Gao, Hongkai; Jägermeyr, Jonas; Senay, Gabriel B.; van Dijk, Albert I. J. M.; Guerschman, Juan P.; Keys, Patrick W.; Gordon, Line J.; Savenije, Hubert H. G.

2016-04-01

This study presents an "Earth observation-based" method for estimating root zone storage capacity - a critical, yet uncertain parameter in hydrological and land surface modelling. By assuming that vegetation optimises its root zone storage capacity to bridge critical dry periods, we were able to use state-of-the-art satellite-based evaporation data computed with independent energy balance equations to derive gridded root zone storage capacity at global scale. This approach does not require soil or vegetation information, is model independent, and is in principle scale independent. In contrast to a traditional look-up table approach, our method captures the variability in root zone storage capacity within land cover types, including in rainforests where direct measurements of root depths otherwise are scarce. Implementing the estimated root zone storage capacity in the global hydrological model STEAM (Simple Terrestrial Evaporation to Atmosphere Model) improved evaporation simulation overall, and in particular during the least evaporating months in sub-humid to humid regions with moderate to high seasonality. Our results suggest that several forest types are able to create a large storage to buffer for severe droughts (with a very long return period), in contrast to, for example, savannahs and woody savannahs (medium length return period), as well as grasslands, shrublands, and croplands (very short return period). The presented method to estimate root zone storage capacity eliminates the need for poor resolution soil and rooting depth data that form a limitation for achieving progress in the global land surface modelling community.

Challenges in simulating the human gut for understanding the role of the microbiota in obesity.

PubMed

Aguirre, M; Venema, K

2017-02-07

There is an elevated incidence of cases of obesity worldwide. Therefore, the development of strategies to tackle this condition is of vital importance. This review focuses on the necessity of optimising in vitro systems to model human colonic fermentation in obese subjects. This may allow to increase the resolution and the physiological relevance of the information obtained from this type of studies when evaluating the potential role that the human gut microbiota plays in obesity. In light of the parameters that are currently used for the in vitro simulation of the human gut (which are mostly based on information derived from healthy subjects) and the possible difference with an obese condition, we propose to revise and improve specific standard operating procedures.

Analysis and design of high-power and efficient, millimeter-wave power amplifier systems using zero degree combiners

NASA Astrophysics Data System (ADS)

Tai, Wei; Abbasi, Mortez; Ricketts, David S.

2018-01-01

We present the analysis and design of high-power millimetre-wave power amplifier (PA) systems using zero-degree combiners (ZDCs). The methodology presented optimises the PA device sizing and the number of combined unit PAs based on device load pull simulations, driver power consumption analysis and loss analysis of the ZDC. Our analysis shows that an optimal number of N-way combined unit PAs leads to the highest power-added efficiency (PAE) for a given output power. To illustrate our design methodology, we designed a 1-W PA system at 45 GHz using a 45 nm silicon-on-insulator process and showed that an 8-way combined PA has the highest PAE that yields simulated output power of 30.6 dBm and 31% peak PAE.

Control allocation-based adaptive control for greenhouse climate

NASA Astrophysics Data System (ADS)

Su, Yuanping; Xu, Lihong; Goodman, Erik D.

2018-04-01

This paper presents an adaptive approach to greenhouse climate control, as part of an integrated control and management system for greenhouse production. In this approach, an adaptive control algorithm is first derived to guarantee the asymptotic convergence of the closed system with uncertainty, then using that control algorithm, a controller is designed to satisfy the demands for heat and mass fluxes to maintain inside temperature, humidity and CO2 concentration at their desired values. Instead of applying the original adaptive control inputs directly, second, a control allocation technique is applied to distribute the demands of the heat and mass fluxes to the actuators by minimising tracking errors and energy consumption. To find an energy-saving solution, both single-objective optimisation (SOO) and multiobjective optimisation (MOO) in the control allocation structure are considered. The advantage of the proposed approach is that it does not require any a priori knowledge of the uncertainty bounds, and the simulation results illustrate the effectiveness of the proposed control scheme. It also indicates that MOO saves more energy in the control process.

A robust detector for rolling element bearing condition monitoring based on the modulation signal bispectrum and its performance evaluation against the Kurtogram

NASA Astrophysics Data System (ADS)

Tian, Xiange; Xi Gu, James; Rehab, Ibrahim; Abdalla, Gaballa M.; Gu, Fengshou; Ball, A. D.

2018-02-01

Envelope analysis is a widely used method for rolling element bearing fault detection. To obtain high detection accuracy, it is critical to determine an optimal frequency narrowband for the envelope demodulation. However, many of the schemes which are used for the narrowband selection, such as the Kurtogram, can produce poor detection results because they are sensitive to random noise and aperiodic impulses which normally occur in practical applications. To achieve the purposes of denoising and frequency band optimisation, this paper proposes a novel modulation signal bispectrum (MSB) based robust detector for bearing fault detection. Because of its inherent noise suppression capability, the MSB allows effective suppression of both stationary random noise and discrete aperiodic noise. The high magnitude features that result from the use of the MSB also enhance the modulation effects of a bearing fault and can be used to provide optimal frequency bands for fault detection. The Kurtogram is generally accepted as a powerful means of selecting the most appropriate frequency band for envelope analysis, and as such it has been used as the benchmark comparator for performance evaluation in this paper. Both simulated and experimental data analysis results show that the proposed method produces more accurate and robust detection results than Kurtogram based approaches for common bearing faults under a range of representative scenarios.

Simulation as a preoperative planning approach in advanced heart failure patients. A retrospective clinical analysis.

PubMed

Capoccia, Massimo; Marconi, Silvia; Singh, Sanjeet Avtaar; Pisanelli, Domenico M; De Lazzari, Claudio

2018-05-02

Modelling and simulation may become clinically applicable tools for detailed evaluation of the cardiovascular system and clinical decision-making to guide therapeutic intervention. Models based on pressure-volume relationship and zero-dimensional representation of the cardiovascular system may be a suitable choice given their simplicity and versatility. This approach has great potential for application in heart failure where the impact of left ventricular assist devices has played a significant role as a bridge to transplant and more recently as a long-term solution for non eligible candidates. We sought to investigate the value of simulation in the context of three heart failure patients with a view to predict or guide further management. CARDIOSIM © was the software used for this purpose. The study was based on retrospective analysis of haemodynamic data previously discussed at a multidisciplinary meeting. The outcome of the simulations addressed the value of a more quantitative approach in the clinical decision process. Although previous experience, co-morbidities and the risk of potentially fatal complications play a role in clinical decision-making, patient-specific modelling may become a daily approach for selection and optimisation of device-based treatment for heart failure patients. Willingness to adopt this integrated approach may be the key to further progress.

Optimisation in the Design of Environmental Sensor Networks with Robustness Consideration

PubMed Central

Budi, Setia; de Souza, Paulo; Timms, Greg; Malhotra, Vishv; Turner, Paul

2015-01-01

This work proposes the design of Environmental Sensor Networks (ESN) through balancing robustness and redundancy. An Evolutionary Algorithm (EA) is employed to find the optimal placement of sensor nodes in the Region of Interest (RoI). Data quality issues are introduced to simulate their impact on the performance of the ESN. Spatial Regression Test (SRT) is also utilised to promote robustness in data quality of the designed ESN. The proposed method provides high network representativeness (fit for purpose) with minimum sensor redundancy (cost), and ensures robustness by enabling the network to continue to achieve its objectives when some sensors fail. PMID:26633392

Reconstruction of hadronic decay products of tau leptons with the ATLAS experiment.

PubMed

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Czirr, H; Czodrowski, P; D'Auria, S; D'Onofrio, M; Da Cunha Sargedas De Sousa, M J; Da Via, C; Dabrowski, W; Dafinca, A; Dai, T; Dale, O; Dallaire, F; Dallapiccola, C; Dam, M; Dandoy, J R; Dang, N P; Daniells, A C; Danninger, M; Dano Hoffmann, M; Dao, V; Darbo, G; Darmora, S; Dassoulas, J; Dattagupta, A; Davey, W; David, C; Davidek, T; Davies, E; Davies, M; Davison, P; Davygora, Y; Dawe, E; Dawson, I; Daya-Ishmukhametova, R K; De, K; de Asmundis, R; De Benedetti, A; De Castro, S; De Cecco, S; De Groot, N; de Jong, P; De la Torre, H; De Lorenzi, F; De Pedis, D; De Salvo, A; De Sanctis, U; De Santo, A; De Vivie De Regie, J B; Dearnaley, W J; Debbe, R; Debenedetti, C; Dedovich, D V; Deigaard, I; Del Peso, J; Del Prete, T; Delgove, D; Deliot, F; Delitzsch, C M; Deliyergiyev, M; Dell'Acqua, A; Dell'Asta, L; Dell'Orso, M; Della Pietra, M; Della Volpe, D; Delmastro, M; Delsart, P A; Deluca, C; DeMarco, D A; Demers, S; Demichev, M; Demilly, A; Denisov, S P; Derendarz, D; Derkaoui, J E; Derue, F; 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Elles, S; Ellinghaus, F; Elliot, A A; Ellis, N; Elmsheuser, J; Elsing, M; Emeliyanov, D; Enari, Y; Endner, O C; Endo, M; Erdmann, J; Ereditato, A; Ernis, G; Ernst, J; Ernst, M; Errede, S; Ertel, E; Escalier, M; Esch, H; Escobar, C; Esposito, B; Etienvre, A I; Etzion, E; Evans, H; Ezhilov, A; Fabbri, L; Facini, G; Fakhrutdinov, R M; Falciano, S; Falla, R J; Faltova, J; Fang, Y; Fanti, M; Farbin, A; Farilla, A; Farooque, T; Farrell, S; Farrington, S M; Farthouat, P; Fassi, F; Fassnacht, P; Fassouliotis, D; Faucci Giannelli, M; Favareto, A; Fayard, L; Fedin, O L; Fedorko, W; Feigl, S; Feligioni, L; Feng, C; Feng, E J; Feng, H; Fenyuk, A B; Feremenga, L; Fernandez Martinez, P; Fernandez Perez, S; Ferrando, J; Ferrari, A; Ferrari, P; Ferrari, R; Ferreira de Lima, D E; Ferrer, A; Ferrere, D; Ferretti, C; Ferretto Parodi, A; Fiascaris, M; Fiedler, F; Filipčič, A; Filipuzzi, M; Filthaut, F; Fincke-Keeler, M; Finelli, K D; Fiolhais, M C N; Fiorini, L; Firan, A; Fischer, A; Fischer, C; Fischer, J; 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Sabato, G; Sacerdoti, S; Saddique, A; Sadrozinski, H F-W; Sadykov, R; Safai Tehrani, F; Saha, P; Sahinsoy, M; Saimpert, M; Saito, T; Sakamoto, H; Sakurai, Y; Salamanna, G; Salamon, A; Salazar Loyola, J E; Saleem, M; Salek, D; Sales De Bruin, P H; Salihagic, D; Salnikov, A; Salt, J; Salvatore, D; Salvatore, F; Salvucci, A; Salzburger, A; Sammel, D; Sampsonidis, D; Sanchez, A; Sánchez, J; Sanchez Martinez, V; Sandaker, H; Sandbach, R L; Sander, H G; Sanders, M P; Sandhoff, M; Sandoval, C; Sandstroem, R; Sankey, D P C; Sannino, M; Sansoni, A; Santoni, C; Santonico, R; Santos, H; Santoyo Castillo, I; Sapp, K; Sapronov, A; Saraiva, J G; Sarrazin, B; Sasaki, O; Sasaki, Y; Sato, K; Sauvage, G; Sauvan, E; Savage, G; Savard, P; Sawyer, C; Sawyer, L; Saxon, J; Sbarra, C; Sbrizzi, A; Scanlon, T; Scannicchio, D A; Scarcella, M; Scarfone, V; Schaarschmidt, J; Schacht, P; Schaefer, D; Schaefer, R; Schaeffer, J; Schaepe, S; Schaetzel, S; Schäfer, U; Schaffer, A C; Schaile, D; Schamberger, R D; Scharf, V; 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Shcherbakova, A; Shehu, C Y; Sherwood, P; Shi, L; Shimizu, S; Shimmin, C O; Shimojima, M; Shiyakova, M; Shmeleva, A; Shoaleh Saadi, D; Shochet, M J; Shojaii, S; Shrestha, S; Shulga, E; Shupe, M A; Sicho, P; Sidebo, P E; Sidiropoulou, O; Sidorov, D; Sidoti, A; Siegert, F; Sijacki, Dj; Silva, J; Silver, Y; Silverstein, S B; Simak, V; Simard, O; Simic, Lj; Simion, S; Simioni, E; Simmons, B; Simon, D; Simon, M; Sinervo, P; Sinev, N B; Sioli, M; Siragusa, G; Sivoklokov, S Yu; Sjölin, J; Sjursen, T B; Skinner, M B; Skottowe, H P; Skubic, P; Slater, M; Slavicek, T; Slawinska, M; Sliwa, K; Smakhtin, V; Smart, B H; Smestad, L; Smirnov, S Yu; Smirnov, Y; Smirnova, L N; Smirnova, O; Smith, M N K; Smith, R W; Smizanska, M; Smolek, K; Snesarev, A A; Snidero, G; Snyder, S; Sobie, R; Socher, F; Soffer, A; Soh, D A; Sokhrannyi, G; Solans, C A; Solar, M; Solc, J; Soldatov, E Yu; Soldevila, U; Solodkov, A A; Soloshenko, A; Solovyanov, O V; Solovyev, V; Sommer, P; Song, H Y; Soni, N; Sood, A; Sopczak, A; Sopko, B; Sopko, V; Sorin, V; Sosa, D; Sosebee, M; Sotiropoulou, C L; Soualah, R; Soukharev, A M; South, D; Sowden, B C; Spagnolo, S; Spalla, M; Spangenberg, M; Spanò, F; Spearman, W R; Sperlich, D; Spettel, F; Spighi, R; Spigo, G; Spiller, L A; Spousta, M; St Denis, R D; Stabile, A; Staerz, S; Stahlman, J; Stamen, R; Stamm, S; Stanecka, E; Stanek, R W; Stanescu, C; Stanescu-Bellu, M; Stanitzki, M M; Stapnes, S; Starchenko, E A; Stark, J; Staroba, P; Starovoitov, P; Staszewski, R; Steinberg, P; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stewart, G A; Stillings, J A; Stockton, M C; Stoebe, M; Stoicea, G; Stolte, P; Stonjek, S; Stradling, A R; Straessner, A; Stramaglia, M E; Strandberg, J; Strandberg, S; Strandlie, A; Strauss, E; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Stroynowski, R; Strubig, A; Stucci, S A; Stugu, B; Styles, N A; Su, D; Su, J; Subramaniam, R; Succurro, A; Suchek, S; Sugaya, Y; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, S; Sun, X; Sundermann, J E; Suruliz, K; Susinno, G; Sutton, M R; Suzuki, S; Svatos, M; Swiatlowski, M; Sykora, I; Sykora, T; Ta, D; Taccini, C; Tackmann, K; Taenzer, J; Taffard, A; Tafirout, R; Taiblum, N; Takai, H; Takashima, R; Takeda, H; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A A; Tam, J Y C; Tan, K G; Tanaka, J; Tanaka, R; Tanaka, S; Tannenwald, B B; Tapia Araya, S; Tapprogge, S; Tarem, S; Tarrade, F; Tartarelli, G F; Tas, P; Tasevsky, M; Tashiro, T; Tassi, E; Tavares Delgado, A; Tayalati, Y; Taylor, A C; Taylor, F E; Taylor, G N; Taylor, P T E; Taylor, W; Teischinger, F A; Teixeira-Dias, P; Temming, K K; Temple, D; Ten Kate, H; Teng, P K; Teoh, J J; Tepel, F; Terada, S; Terashi, K; Terron, J; Terzo, S; Testa, M; Teuscher, R J; Theveneaux-Pelzer, T; Thomas, J P; Thomas-Wilsker, J; Thompson, E N; Thompson, P D; Thompson, R J; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Thun, R P; Tibbetts, M J; Ticse Torres, R E; Tikhomirov, V O; Tikhonov, Yu A; Timoshenko, S; Tiouchichine, E; Tipton, P; Tisserant, S; Todome, K; Todorov, T; Todorova-Nova, S; Tojo, J; Tokár, S; Tokushuku, K; Tollefson, K; Tolley, E; Tomlinson, L; Tomoto, M; Tompkins, L; Toms, K; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Trefzger, T; Tremblet, L; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Tripiana, M F; Trischuk, W; Trocmé, B; Troncon, C; Trottier-McDonald, M; Trovatelli, M; Truong, L; Trzebinski, M; Trzupek, A; Tsarouchas, C; Tseng, J C-L; Tsiareshka, P V; Tsionou, D; Tsipolitis, G; Tsirintanis, N; Tsiskaridze, S; Tsiskaridze, V; Tskhadadze, E G; Tsui, K M; Tsukerman, I I; Tsulaia, V; Tsuno, S; Tsybychev, D; Tudorache, A; Tudorache, V; Tuna, A N; Tupputi, S A; Turchikhin, S; Turecek, D; Turra, R; Turvey, A J; Tuts, P M; Tykhonov, A; Tylmad, M; Tyndel, M; Ueda, I; Ueno, R; Ughetto, M; Ukegawa, F; Unal, G; Undrus, A; Unel, G; Ungaro, F C; Unno, Y; Unverdorben, C; Urban, J; Urquijo, P; Urrejola, P; Usai, G; Usanova, A; Vacavant, L; Vacek, V; Vachon, B; Valderanis, C; Valencic, N; Valentinetti, S; 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Zhu, J; Zhu, Y; Zhuang, X; Zhukov, K; Zibell, A; Zieminska, D; Zimine, N I; Zimmermann, C; Zimmermann, S; Zinonos, Z; Zinser, M; Ziolkowski, M; Živković, L; Zobernig, G; Zoccoli, A; Zur Nedden, M; Zurzolo, G; Zwalinski, L

2016-01-01

This paper presents a new method of reconstructing the individual charged and neutral hadrons in tau decays with the ATLAS detector. The reconstructed hadrons are used to classify the decay mode and to calculate the visible four-momentum of reconstructed tau candidates, significantly improving the resolution with respect to the calibration in the existing tau reconstruction. The performance of the reconstruction algorithm is optimised and evaluated using simulation and validated using samples of [Formula: see text] and [Formula: see text]+jets events selected from proton-proton collisions at a centre-of-mass energy [Formula: see text], corresponding to an integrated luminosity of 5 [Formula: see text].

Emergency Management Operations Process Mapping: Public Safety Technical Program Study

DTIC Science & Technology

2011-02-01

Enterprise Architectures in industry, and have been successfully applied to assist companies to optimise interdependencies and relationships between...model for more in-depth analysis of EM processes, and for use in tandem with other studies that apply modeling and simulation to assess EM...for use in tandem with other studies that apply modeling and simulation to assess EM operational effectiveness before and after changing elements

Optimising probe holder design for sentinel lymph node imaging using clinical photoacoustic system with Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Sivasubramanian, Kathyayini; Periyasamy, Vijitha; Wen, Kew Kok; Pramanik, Manojit

2017-03-01

Photoacoustic tomography is a hybrid imaging modality that combines optical and ultrasound imaging. It is rapidly gaining attention in the field of medical imaging. The challenge is to translate it into a clinical setup. In this work, we report the development of a handheld clinical photoacoustic imaging system. A clinical ultrasound imaging system is modified to integrate photoacoustic imaging with the ultrasound imaging. Hence, light delivery has been integrated with the ultrasound probe. The angle of light delivery is optimized in this work with respect to the depth of imaging. Optimization was performed based on Monte Carlo simulation for light transport in tissues. Based on the simulation results, the probe holders were fabricated using 3D printing. Similar results were obtained experimentally using phantoms. Phantoms were developed to mimic sentinel lymph node imaging scenario. Also, in vivo sentinel lymph node imaging was done using the same system with contrast agent methylene blue up to a depth of 1.5 cm. The results validate that one can use Monte Carlo simulation as a tool to optimize the probe holder design depending on the imaging needs. This eliminates a trial and error approach generally used for designing a probe holder.

Structural optimisation of cage induction motors using finite element analysis

NASA Astrophysics Data System (ADS)

Palko, S.

The current trend in motor design is to have highly efficient, low noise, low cost, and modular motors with a high power factor. High torque motors are useful in applications like servo motors, lifts, cranes, and rolling mills. This report contains a detailed review of different optimization methods applicable in various design problems. Special attention is given to the performance of different methods, when they are used with finite element analysis (FEA) as an objective function, and accuracy problems arising from the numerical simulations. Also an effective method for designing high starting torque and high efficiency motors is presented. The method described in this work utilizes FEA combined with algorithms for the optimization of the slot geometry. The optimization algorithm modifies the position of the nodal points in the element mesh. The number of independent variables ranges from 14 to 140 in this work.

rPM6 parameters for phosphorous and sulphur-containing open-shell molecules

NASA Astrophysics Data System (ADS)

Saito, Toru; Takano, Yu

2018-03-01

In this article, we have introduced a reparameterisation of PM6 (rPM6) for phosphorus and sulphur to achieve a better description of open-shell species containing the two elements. Two sets of the parameters have been optimised separately using our training sets. The performance of the spin-unrestricted rPM6 (UrPM6) method with the optimised parameters is evaluated against 14 radical species, which contain either phosphorus or sulphur atom, comparing with the original UPM6 and the spin-unrestricted density functional theory (UDFT) methods. The standard UPM6 calculations fail to describe the adiabatic singlet-triplet energy gaps correctly, and may cause significant structural mismatches with UDFT-optimised geometries. Leaving aside three difficult cases, tests on 11 open-shell molecules strongly indicate the superior performance of UrPM6, which provides much better agreement with the results of UDFT methods for geometric and electronic properties.

Dynamic VMs placement for energy efficiency by PSO in cloud computing

NASA Astrophysics Data System (ADS)

Dashti, Seyed Ebrahim; Rahmani, Amir Masoud

2016-03-01

Recently, cloud computing is growing fast and helps to realise other high technologies. In this paper, we propose a hieratical architecture to satisfy both providers' and consumers' requirements in these technologies. We design a new service in the PaaS layer for scheduling consumer tasks. In the providers' perspective, incompatibility between specification of physical machine and user requests in cloud leads to problems such as energy-performance trade-off and large power consumption so that profits are decreased. To guarantee Quality of service of users' tasks, and reduce energy efficiency, we proposed to modify Particle Swarm Optimisation to reallocate migrated virtual machines in the overloaded host. We also dynamically consolidate the under-loaded host which provides power saving. Simulation results in CloudSim demonstrated that whatever simulation condition is near to the real environment, our method is able to save as much as 14% more energy and the number of migrations and simulation time significantly reduces compared with the previous works.

Optimisation of cavity parameters for lasers based on AlGaInAsP/InP solid solutions (λ = 1470 nm)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Veselov, D A; Ayusheva, K R; Shashkin, I S

2015-10-31

We have studied the effect of laser cavity parameters on the light–current characteristics of lasers based on the AlGaInAs/GaInAsP/InP solid solution system that emit in the spectral range 1400 – 1600 nm. It has been shown that optimisation of cavity parameters (chip length and front facet reflectivity) allows one to improve heat removal from the laser, without changing other laser characteristics. An increase in the maximum output optical power of the laser by 0.5 W has been demonstrated due to cavity design optimisation. (lasers)

A water market simulator considering pair-wise trades between agents

NASA Astrophysics Data System (ADS)

Huskova, I.; Erfani, T.; Harou, J. J.

2012-04-01

In many basins in England no further water abstraction licences are available. Trading water between water rights holders has been recognized as a potentially effective and economically efficient strategy to mitigate increasing scarcity. A screening tool that could assess the potential for trade through realistic simulation of individual water rights holders would help assess the solution's potential contribution to local water management. We propose an optimisation-driven water market simulator that predicts pair-wise trade in a catchment and represents its interaction with natural hydrology and engineered infrastructure. A model is used to emulate licence-holders' willingness to engage in short-term trade transactions. In their simplest form agents are represented using an economic benefit function. The working hypothesis is that trading behaviour can be partially predicted based on differences in marginal values of water over space and time and estimates of transaction costs on pair-wise trades. We discuss the further possibility of embedding rules, norms and preferences of the different water user sectors to more realistically represent the behaviours, motives and constraints of individual licence holders. The potential benefits and limitations of such a social simulation (agent-based) approach is contrasted with our simulator where agents are driven by economic optimization. A case study based on the Dove River Basin (UK) demonstrates model inputs and outputs. The ability of the model to suggest impacts of water rights policy reforms on trading is discussed.

A simple model clarifies the complicated relationships of complex networks

PubMed Central

Zheng, Bojin; Wu, Hongrun; Kuang, Li; Qin, Jun; Du, Wenhua; Wang, Jianmin; Li, Deyi

2014-01-01

Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it is widely believed that these traits origin from different causes. However, we find that a simple model based on optimisation can produce many traits, including scale-free, small-world, ultra small-world, Delta-distribution, compact, fractal, regular and random networks. Moreover, by revising the proposed model, the community-structure networks are generated. By this model and the revised versions, the complicated relationships of complex networks are illustrated. The model brings a new universal perspective to the understanding of complex networks and provide a universal method to model complex networks from the viewpoint of optimisation. PMID:25160506

A waste characterisation procedure for ADM1 implementation based on degradation kinetics.

PubMed

Girault, R; Bridoux, G; Nauleau, F; Poullain, C; Buffet, J; Steyer, J-P; Sadowski, A G; Béline, F

2012-09-01

In this study, a procedure accounting for degradation kinetics was developed to split the total COD of a substrate into each input state variable required for Anaerobic Digestion Model n°1. The procedure is based on the combination of batch experimental degradation tests ("anaerobic respirometry") and numerical interpretation of the results obtained (optimisation of the ADM1 input state variable set). The effects of the main operating parameters, such as the substrate to inoculum ratio in batch experiments and the origin of the inoculum, were investigated. Combined with biochemical fractionation of the total COD of substrates, this method enabled determination of an ADM1-consistent input state variable set for each substrate with affordable identifiability. The substrate to inoculum ratio in the batch experiments and the origin of the inoculum influenced input state variables. However, based on results modelled for a CSTR fed with the substrate concerned, these effects were not significant. Indeed, if the optimal ranges of these operational parameters are respected, uncertainty in COD fractionation is mainly limited to temporal variability of the properties of the substrates. As the method is based on kinetics and is easy to implement for a wide range of substrates, it is a very promising way to numerically predict the effect of design parameters on the efficiency of an anaerobic CSTR. This method thus promotes the use of modelling for the design and optimisation of anaerobic processes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Modelling soil water retention using support vector machines with genetic algorithm optimisation.

PubMed

Lamorski, Krzysztof; Sławiński, Cezary; Moreno, Felix; Barna, Gyöngyi; Skierucha, Wojciech; Arrue, José L

2014-01-01

This work presents point pedotransfer function (PTF) models of the soil water retention curve. The developed models allowed for estimation of the soil water content for the specified soil water potentials: -0.98, -3.10, -9.81, -31.02, -491.66, and -1554.78 kPa, based on the following soil characteristics: soil granulometric composition, total porosity, and bulk density. Support Vector Machines (SVM) methodology was used for model development. A new methodology for elaboration of retention function models is proposed. Alternative to previous attempts known from literature, the ν-SVM method was used for model development and the results were compared with the formerly used the C-SVM method. For the purpose of models' parameters search, genetic algorithms were used as an optimisation framework. A new form of the aim function used for models parameters search is proposed which allowed for development of models with better prediction capabilities. This new aim function avoids overestimation of models which is typically encountered when root mean squared error is used as an aim function. Elaborated models showed good agreement with measured soil water retention data. Achieved coefficients of determination values were in the range 0.67-0.92. Studies demonstrated usability of ν-SVM methodology together with genetic algorithm optimisation for retention modelling which gave better performing models than other tested approaches.

Optimising Habitat-Based Models for Wide-Ranging Marine Predators: Scale Matters

NASA Astrophysics Data System (ADS)

Scales, K. L.; Hazen, E. L.; Jacox, M.; Edwards, C. A.; Bograd, S. J.

2016-12-01

Predicting the responses of marine top predators to dynamic oceanographic conditions requires habitat-based models that sufficiently capture environmental preferences. Spatial resolution and temporal averaging of environmental data layers is a key aspect of model construction. The utility of surfaces contemporaneous to animal movement (e.g. daily, weekly), versus synoptic products (monthly, seasonal, climatological) is currently under debate, as is the optimal spatial resolution for predictive products. Using movement simulations with built-in environmental preferences (correlated random walks, multi-state hidden Markov-type models) together with modeled (Regional Oceanographic Modeling System, ROMS) and remotely-sensed (MODIS-Aqua) datasets, we explored the effects of degrading environmental surfaces (3km - 1 degree, daily - climatological) on model inference. We simulated the movements of a hypothetical wide-ranging marine predator through the California Current system over a three month period (May-June-July), based on metrics derived from previously published blue whale Balaenoptera musculus tracking studies. Results indicate that models using seasonal or climatological data fields can overfit true environmental preferences, in both presence-absence and behaviour-based model formulations. Moreover, the effects of a degradation in spatial resolution are more pronounced when using temporally averaged fields than when using daily, weekly or monthly datasets. In addition, we observed a notable divergence between the `best' models selected using common methods (e.g. AUC, AICc) and those that most accurately reproduced built-in environmental preferences. These findings have important implications for conservation and management of marine mammals, seabirds, sharks, sea turtles and large teleost fish, particularly in implementing dynamic ocean management initiatives and in forecasting responses to future climate-mediated ecosystem change.

Optimising Habitat-Based Models for Wide-Ranging Marine Predators: Scale Matters

NASA Astrophysics Data System (ADS)

Scales, K. L.; Hazen, E. L.; Jacox, M.; Edwards, C. A.; Bograd, S. J.

2016-02-01

Predicting the responses of marine top predators to dynamic oceanographic conditions requires habitat-based models that sufficiently capture environmental preferences. Spatial resolution and temporal averaging of environmental data layers is a key aspect of model construction. The utility of surfaces contemporaneous to animal movement (e.g. daily, weekly), versus synoptic products (monthly, seasonal, climatological) is currently under debate, as is the optimal spatial resolution for predictive products. Using movement simulations with built-in environmental preferences (correlated random walks, multi-state hidden Markov-type models) together with modeled (Regional Oceanographic Modeling System, ROMS) and remotely-sensed (MODIS-Aqua) datasets, we explored the effects of degrading environmental surfaces (3km - 1 degree, daily - climatological) on model inference. We simulated the movements of a hypothetical wide-ranging marine predator through the California Current system over a three month period (May-June-July), based on metrics derived from previously published blue whale Balaenoptera musculus tracking studies. Results indicate that models using seasonal or climatological data fields can overfit true environmental preferences, in both presence-absence and behaviour-based model formulations. Moreover, the effects of a degradation in spatial resolution are more pronounced when using temporally averaged fields than when using daily, weekly or monthly datasets. In addition, we observed a notable divergence between the `best' models selected using common methods (e.g. AUC, AICc) and those that most accurately reproduced built-in environmental preferences. These findings have important implications for conservation and management of marine mammals, seabirds, sharks, sea turtles and large teleost fish, particularly in implementing dynamic ocean management initiatives and in forecasting responses to future climate-mediated ecosystem change.

A CONCEPTUAL FRAMEWORK FOR MANAGING RADIATION DOSE TO PATIENTS IN DIAGNOSTIC RADIOLOGY USING REFERENCE DOSE LEVELS.

PubMed

Almén, Anja; Båth, Magnus

2016-06-01

The overall aim of the present work was to develop a conceptual framework for managing radiation dose in diagnostic radiology with the intention to support optimisation. An optimisation process was first derived. The framework for managing radiation dose, based on the derived optimisation process, was then outlined. The outset of the optimisation process is four stages: providing equipment, establishing methodology, performing examinations and ensuring quality. The optimisation process comprises a series of activities and actions at these stages. The current system of diagnostic reference levels is an activity in the last stage, ensuring quality. The system becomes a reactive activity only to a certain extent engaging the core activity in the radiology department, performing examinations. Three reference dose levels-possible, expected and established-were assigned to the three stages in the optimisation process, excluding ensuring quality. A reasonably achievable dose range is also derived, indicating an acceptable deviation from the established dose level. A reasonable radiation dose for a single patient is within this range. The suggested framework for managing radiation dose should be regarded as one part of the optimisation process. The optimisation process constitutes a variety of complementary activities, where managing radiation dose is only one part. This emphasises the need to take a holistic approach integrating the optimisation process in different clinical activities. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Development and validation of a rapid capillary zone electrophoresis method for the determination of aconite alkaloids in aconite roots.

PubMed

Song, Jing-Zheng; Han, Quan-Bin; Qiao, Chun-Feng; But, Paul Pui-Hay; Xu, Hong-Xi

2010-01-01

Aconites, with aconite alkaloids as the major therapeutic and toxic components, are used for the treatment of analgesic, antirheumatic and neurological symptoms. Quantification of the aconite alkaloids is important for the quality control of aconite-containing drugs. To establish a validated capillary zone electrophoresis (CZE) method for the simultaneous determination of six major alkaloids, namely aconitine, mesaconitine, hypaconitine, benzoylaconine, benzoylmesaconine and benzoylhypaconine, in crude and processed aconite roots. The CZE method was optimised and validated using a stability-indicating method. The optimised running buffer was a mixture of 200 mm Tris, 150 mm perchloric acid and 40% 1,4-dioxane (pH 7.8) with the capillary thermostated at 25 degrees C. Using the optimised method, six aconite alkaloids were well separated. The established method showed good precision, accuracy and recovery. Contents of these alkaloids in crude and processed aconites were determined and it was observed that the levels of individual alkaloids varied between samples. The developed CZE method was reliable for the quality control of aconites contained in herbal medicines. The method could also be used as an approach for toxicological studies.

Selecting a climate model subset to optimise key ensemble properties

NASA Astrophysics Data System (ADS)

Herger, Nadja; Abramowitz, Gab; Knutti, Reto; Angélil, Oliver; Lehmann, Karsten; Sanderson, Benjamin M.

2018-02-01

End users studying impacts and risks caused by human-induced climate change are often presented with large multi-model ensembles of climate projections whose composition and size are arbitrarily determined. An efficient and versatile method that finds a subset which maintains certain key properties from the full ensemble is needed, but very little work has been done in this area. Therefore, users typically make their own somewhat subjective subset choices and commonly use the equally weighted model mean as a best estimate. However, different climate model simulations cannot necessarily be regarded as independent estimates due to the presence of duplicated code and shared development history. Here, we present an efficient and flexible tool that makes better use of the ensemble as a whole by finding a subset with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments. This approach is illustrated with one set of optimisation criteria but we also highlight the flexibility of cost functions, depending on the focus of different users. The technique is useful for a range of applications that, for example, minimise present-day bias to obtain an accurate ensemble mean, reduce dependence in ensemble spread, maximise future spread, ensure good performance of individual models in an ensemble, reduce the ensemble size while maintaining important ensemble characteristics, or optimise several of these at the same time. As in any calibration exercise, the final ensemble is sensitive to the metric, observational product, and pre-processing steps used.

Optimisation of DNA extraction from the crustacean Daphnia

PubMed Central

Athanasio, Camila Gonçalves; Chipman, James K.; Viant, Mark R.

2016-01-01

Daphnia are key model organisms for mechanistic studies of phenotypic plasticity, adaptation and microevolution, which have led to an increasing demand for genomics resources. A key step in any genomics analysis, such as high-throughput sequencing, is the availability of sufficient and high quality DNA. Although commercial kits exist to extract genomic DNA from several species, preparation of high quality DNA from Daphnia spp. and other chitinous species can be challenging. Here, we optimise methods for tissue homogenisation, DNA extraction and quantification customised for different downstream analyses (e.g., LC-MS/MS, Hiseq, mate pair sequencing or Nanopore). We demonstrate that if Daphnia magna are homogenised as whole animals (including the carapace), absorbance-based DNA quantification methods significantly over-estimate the amount of DNA, resulting in using insufficient starting material for experiments, such as preparation of sequencing libraries. This is attributed to the high refractive index of chitin in Daphnia’s carapace at 260 nm. Therefore, unless the carapace is removed by overnight proteinase digestion, the extracted DNA should be quantified with fluorescence-based methods. However, overnight proteinase digestion will result in partial fragmentation of DNA therefore the prepared DNA is not suitable for downstream methods that require high molecular weight DNA, such as PacBio, mate pair sequencing and Nanopore. In conclusion, we found that the MasterPure DNA purification kit, coupled with grinding of frozen tissue, is the best method for extraction of high molecular weight DNA as long as the extracted DNA is quantified with fluorescence-based methods. This method generated high yield and high molecular weight DNA (3.10 ± 0.63 ng/µg dry mass, fragments >60 kb), free of organic contaminants (phenol, chloroform) and is suitable for large number of downstream analyses. PMID:27190714

SpaceInn hare-and-hounds exercise: Estimation of stellar properties using space-based asteroseismic data

NASA Astrophysics Data System (ADS)

Reese, D. R.; Chaplin, W. J.; Davies, G. R.; Miglio, A.; Antia, H. M.; Ball, W. H.; Basu, S.; Buldgen, G.; Christensen-Dalsgaard, J.; Coelho, H. R.; Hekker, S.; Houdek, G.; Lebreton, Y.; Mazumdar, A.; Metcalfe, T. S.; Silva Aguirre, V.; Stello, D.; Verma, K.

2016-07-01

Context. Detailed oscillation spectra comprising individual frequencies for numerous solar-type stars and red giants are either currently available, e.g. courtesy of the CoRoT, Kepler, and K2 missions, or will become available with the upcoming NASA TESS and ESA PLATO 2.0 missions. The data can lead to a precise characterisation of these stars thereby improving our understanding of stellar evolution, exoplanetary systems, and the history of our galaxy. Aims: Our goal is to test and compare different methods for obtaining stellar properties from oscillation frequencies and spectroscopic constraints. Specifically, we would like to evaluate the accuracy of the results and reliability of the associated error bars, and to see where there is room for improvement. Methods: In the context of the SpaceInn network, we carried out a hare-and-hounds exercise in which one group, the hares, simulated observations of oscillation spectra for a set of ten artificial solar-type stars, and a number of hounds applied various methods for characterising these stars based on the data produced by the hares. Most of the hounds fell into two main groups. The first group used forward modelling (I.e. applied various search/optimisation algorithms in a stellar parameter space) whereas the second group relied on acoustic glitch signatures. Results: Results based on the forward modelling approach were accurate to 1.5% (radius), 3.9% (mass), 23% (age), 1.5% (surface gravity), and 1.8% (mean density), as based on the root mean square difference. Individual hounds reached different degrees of accuracy, some of which were substantially better than the above average values. For the two 1M⊙ stellar targets, the accuracy on the age is better than 10% thereby satisfying the requirements for the PLATO 2.0 mission. High stellar masses and atomic diffusion (which in our models does not include the effects of radiative accelerations) proved to be sources of difficulty. The average accuracies for the acoustic radii of the base of the convection zone, the He II ionisation, and the Γ1 peak located between the two He ionisation zones were 17%, 2.4%, and 1.9%, respectively. The results from the forward modelling were on average more accurate than those from the glitch fitting analysis as the latter seemed to be affected by aliasing problems for some of the targets. Conclusions: Our study indicates that forward modelling is the most accurate way of interpreting the pulsation spectra of solar-type stars. However, given its model-dependent nature, this method needs to be complemented by model-independent results from, e.g. glitch analysis. Furthermore, our results indicate that global rather than local optimisation algorithms should be used in order to obtain robust error bars.

Thermal buckling optimisation of composite plates using firefly algorithm

NASA Astrophysics Data System (ADS)

Kamarian, S.; Shakeri, M.; Yas, M. H.

2017-07-01

Composite plates play a very important role in engineering applications, especially in aerospace industry. Thermal buckling of such components is of great importance and must be known to achieve an appropriate design. This paper deals with stacking sequence optimisation of laminated composite plates for maximising the critical buckling temperature using a powerful meta-heuristic algorithm called firefly algorithm (FA) which is based on the flashing behaviour of fireflies. The main objective of present work was to show the ability of FA in optimisation of composite structures. The performance of FA is compared with the results reported in the previous published works using other algorithms which shows the efficiency of FA in stacking sequence optimisation of laminated composite structures.

Variational Bayesian identification and prediction of stochastic nonlinear dynamic causal models.

PubMed

Daunizeau, J; Friston, K J; Kiebel, S J

2009-11-01

In this paper, we describe a general variational Bayesian approach for approximate inference on nonlinear stochastic dynamic models. This scheme extends established approximate inference on hidden-states to cover: (i) nonlinear evolution and observation functions, (ii) unknown parameters and (precision) hyperparameters and (iii) model comparison and prediction under uncertainty. Model identification or inversion entails the estimation of the marginal likelihood or evidence of a model. This difficult integration problem can be finessed by optimising a free-energy bound on the evidence using results from variational calculus. This yields a deterministic update scheme that optimises an approximation to the posterior density on the unknown model variables. We derive such a variational Bayesian scheme in the context of nonlinear stochastic dynamic hierarchical models, for both model identification and time-series prediction. The computational complexity of the scheme is comparable to that of an extended Kalman filter, which is critical when inverting high dimensional models or long time-series. Using Monte-Carlo simulations, we assess the estimation efficiency of this variational Bayesian approach using three stochastic variants of chaotic dynamic systems. We also demonstrate the model comparison capabilities of the method, its self-consistency and its predictive power.

Elitist Binary Wolf Search Algorithm for Heuristic Feature Selection in High-Dimensional Bioinformatics Datasets.

PubMed

Li, Jinyan; Fong, Simon; Wong, Raymond K; Millham, Richard; Wong, Kelvin K L

2017-06-28

Due to the high-dimensional characteristics of dataset, we propose a new method based on the Wolf Search Algorithm (WSA) for optimising the feature selection problem. The proposed approach uses the natural strategy established by Charles Darwin; that is, 'It is not the strongest of the species that survives, but the most adaptable'. This means that in the evolution of a swarm, the elitists are motivated to quickly obtain more and better resources. The memory function helps the proposed method to avoid repeat searches for the worst position in order to enhance the effectiveness of the search, while the binary strategy simplifies the feature selection problem into a similar problem of function optimisation. Furthermore, the wrapper strategy gathers these strengthened wolves with the classifier of extreme learning machine to find a sub-dataset with a reasonable number of features that offers the maximum correctness of global classification models. The experimental results from the six public high-dimensional bioinformatics datasets tested demonstrate that the proposed method can best some of the conventional feature selection methods up to 29% in classification accuracy, and outperform previous WSAs by up to 99.81% in computational time.

Consideration of plant behaviour in optimal servo-compensator design

NASA Astrophysics Data System (ADS)

Moase, W. H.; Manzie, C.

2016-07-01

Where the most prevalent optimal servo-compensator formulations penalise the behaviour of an error system, this paper considers the problem of additionally penalising the actual states and inputs of the plant. Doing so has the advantage of enabling the penalty function to better resemble an economic cost. This is especially true of problems where control effort needs to be sensibly allocated across weakly redundant inputs or where one wishes to use penalties to soft-constrain certain states or inputs. It is shown that, although the resulting cost function grows unbounded as its horizon approaches infinity, it is possible to formulate an equivalent optimisation problem with a bounded cost. The resulting optimisation problem is similar to those in earlier studies but has an additional 'correction term' in the cost function, and a set of equality constraints that arise when there are redundant inputs. A numerical approach to solve the resulting optimisation problem is presented, followed by simulations on a micro-macro positioner that illustrate the benefits of the proposed servo-compensator design approach.

Path optimisation of a mobile robot using an artificial neural network controller

NASA Astrophysics Data System (ADS)

Singh, M. K.; Parhi, D. R.

2011-01-01

This article proposed a novel approach for design of an intelligent controller for an autonomous mobile robot using a multilayer feed forward neural network, which enables the robot to navigate in a real world dynamic environment. The inputs to the proposed neural controller consist of left, right and front obstacle distance with respect to its position and target angle. The output of the neural network is steering angle. A four layer neural network has been designed to solve the path and time optimisation problem of mobile robots, which deals with the cognitive tasks such as learning, adaptation, generalisation and optimisation. A back propagation algorithm is used to train the network. This article also analyses the kinematic design of mobile robots for dynamic movements. The simulation results are compared with experimental results, which are satisfactory and show very good agreement. The training of the neural nets and the control performance analysis has been done in a real experimental setup.

Development and optimisation of an HPLC-DAD-ESI-Q-ToF method for the determination of phenolic acids and derivatives.

PubMed

Restivo, Annalaura; Degano, Ilaria; Ribechini, Erika; Colombini, Maria Perla

2014-01-01

A method for the HPLC-MS/MS analysis of phenols, including phenolic acids and naphtoquinones, using an amide-embedded phase column was developed and compared to the literature methods based on classical C18 stationary phase columns. RP-Amide is a recently developed polar embedded stationary phase, whose wetting properties mean that up to 100% water can be used as an eluent. The increased retention and selectivity for polar compounds and the possibility of working in 100% water conditions make this column particularly interesting for the HPLC analysis of phenolic acids and derivatives. In this study, the chromatographic separation was optimised on an HPLC-DAD, and was used to separate 13 standard phenolic acids and derivatives. The method was validated on an HPLC-ESI-Q-ToF. The acquisition was performed in negative polarity and MS/MS target mode. Ionisation conditions and acquisition parameters for the Q-ToF detector were investigated by working on collision energies and fragmentor potentials. The performance of the method was fully evaluated on standards. Moreover, several raw materials containing phenols were analysed: walnut, gall, wine, malbec grape, French oak, red henna and propolis. Our method allowed us to characterize the phenolic composition in a wide range of matrices and to highlight possible matrix effects.

Magneto-acoustic imaging by continuous-wave excitation.

PubMed

Shunqi, Zhang; Zhou, Xiaoqing; Tao, Yin; Zhipeng, Liu

2017-04-01

The electrical characteristics of tissue yield valuable information for early diagnosis of pathological changes. Magneto-acoustic imaging is a functional approach for imaging of electrical conductivity. This study proposes a continuous-wave magneto-acoustic imaging method. A kHz-range continuous signal with an amplitude range of several volts is used to excite the magneto-acoustic signal and improve the signal-to-noise ratio. The magneto-acoustic signal amplitude and phase are measured to locate the acoustic source via lock-in technology. An optimisation algorithm incorporating nonlinear equations is used to reconstruct the magneto-acoustic source distribution based on the measured amplitude and phase at various frequencies. Validation simulations and experiments were performed in pork samples. The experimental and simulation results agreed well. While the excitation current was reduced to 10 mA, the acoustic signal magnitude increased up to 10 -7  Pa. Experimental reconstruction of the pork tissue showed that the image resolution reached mm levels when the excitation signal was in the kHz range. The signal-to-noise ratio of the detected magneto-acoustic signal was improved by more than 25 dB at 5 kHz when compared to classical 1 MHz pulse excitation. The results reported here will aid further research into magneto-acoustic generation mechanisms and internal tissue conductivity imaging.

New Trends in Forging Technologies

NASA Astrophysics Data System (ADS)

Behrens, B.-A.; Hagen, T.; Knigge, J.; Elgaly, I.; Hadifi, T.; Bouguecha, A.

2011-05-01

Limited natural resources increase the demand on highly efficient machinery and transportation means. New energy-saving mobility concepts call for design optimisation through downsizing of components and choice of corrosion resistant materials possessing high strength to density ratios. Component downsizing can be performed either by constructive structural optimisation or by substituting heavy materials with lighter high-strength ones. In this context, forging plays an important role in manufacturing load-optimised structural components. At the Institute of Metal Forming and Metal-Forming Machines (IFUM) various innovative forging technologies have been developed. With regard to structural optimisation, different strategies for localised reinforcement of components were investigated. Locally induced strain hardening by means of cold forging under a superimposed hydrostatic pressure could be realised. In addition, controlled martensitic zones could be created through forming induced phase conversion in metastable austenitic steels. Other research focused on the replacement of heavy steel parts with high-strength nonferrous alloys or hybrid material compounds. Several forging processes of magnesium, aluminium and titanium alloys for different aeronautical and automotive applications were developed. The whole process chain from material characterisation via simulation-based process design to the production of the parts has been considered. The feasibility of forging complex shaped geometries using these alloys was confirmed. In spite of the difficulties encountered due to machine noise and high temperature, acoustic emission (AE) technique has been successfully applied for online monitoring of forging defects. New AE analysis algorithm has been developed, so that different signal patterns due to various events such as product/die cracking or die wear could be detected and classified. Further, the feasibility of the mentioned forging technologies was proven by means of the finite element analysis (FEA). For example, the integrity of forging dies with respect to crack initiation due to thermo-mechanical fatigue as well as the ductile damage of forgings was investigated with the help of cumulative damage models. In this paper some of the mentioned approaches are described.

Stability analysis using SDSA tool

NASA Astrophysics Data System (ADS)

Goetzendorf-Grabowski, Tomasz; Mieszalski, Dawid; Marcinkiewicz, Ewa

2011-11-01

The SDSA (Simulation and Dynamic Stability Analysis) application is presented as a tool for analysing the dynamic characteristics of the aircraft just in the conceptual design stage. SDSA is part of the CEASIOM (Computerized Environment for Aircraft Synthesis and Integrated Optimization Methods) software environment which was developed within the SimSAC (Simulating Aircraft Stability And Control Characteristics for Use in Conceptual Design) project, funded by the European Commission 6th Framework Program. SDSA can also be used as stand alone software, and integrated with other design and optimisation systems using software wrappers. This paper focuses on the main functionalities of SDSA and presents both computational and free flight experimental results to compare and validate the presented software. Two aircraft are considered, the EADS Ranger 2000 and the Warsaw University designed PW-6 glider. For the two cases considered here the SDSA software is shown to be an excellent tool for predicting dynamic characteristics of an aircraft.

Separable projection integrals for higher-order correlators of the cosmic microwave sky: Acceleration by factors exceeding 100

NASA Astrophysics Data System (ADS)

Briggs, J. P.; Pennycook, S. J.; Fergusson, J. R.; Jäykkä, J.; Shellard, E. P. S.

2016-04-01

We present a case study describing efforts to optimise and modernise "Modal", the simulation and analysis pipeline used by the Planck satellite experiment for constraining general non-Gaussian models of the early universe via the bispectrum (or three-point correlator) of the cosmic microwave background radiation. We focus on one particular element of the code: the projection of bispectra from the end of inflation to the spherical shell at decoupling, which defines the CMB we observe today. This code involves a three-dimensional inner product between two functions, one of which requires an integral, on a non-rectangular domain containing a sparse grid. We show that by employing separable methods this calculation can be reduced to a one-dimensional summation plus two integrations, reducing the overall dimensionality from four to three. The introduction of separable functions also solves the issue of the non-rectangular sparse grid. This separable method can become unstable in certain scenarios and so the slower non-separable integral must be calculated instead. We present a discussion of the optimisation of both approaches. We demonstrate significant speed-ups of ≈100×, arising from a combination of algorithmic improvements and architecture-aware optimisations targeted at improving thread and vectorisation behaviour. The resulting MPI/OpenMP hybrid code is capable of executing on clusters containing processors and/or coprocessors, with strong-scaling efficiency of 98.6% on up to 16 nodes. We find that a single coprocessor outperforms two processor sockets by a factor of 1.3× and that running the same code across a combination of both microarchitectures improves performance-per-node by a factor of 3.38×. By making bispectrum calculations competitive with those for the power spectrum (or two-point correlator) we are now able to consider joint analysis for cosmological science exploitation of new data.

Development of a Gas Dynamic and Thermodynamic Simulation Model of the Lontra Blade Compressor™

NASA Astrophysics Data System (ADS)

Karlovsky, Jerome

2015-08-01

The Lontra Blade Compressor™ is a patented double acting, internally compressing, positive displacement rotary compressor of innovative design. The Blade Compressor is in production for waste-water treatment, and will soon be launched for a range of applications at higher pressure ratios. In order to aid the design and development process, a thermodynamic and gas dynamic simulation program has been written in house. The software has been successfully used to optimise geometries and running conditions of current designs, and is also being used to evaluate future designs for different applications and markets. The simulation code has three main elements. A positive displacement chamber model, a leakage model and a gas dynamic model to simulate gas flow through ports and to track pressure waves in the inlet and outlet pipes. All three of these models are interlinked in order to track mass and energy flows within the system. A correlation study has been carried out to verify the software. The main correlation markers used were mass flow, chamber pressure, pressure wave tracking in the outlet pipe, and volumetric efficiency. It will be shown that excellent correlation has been achieved between measured and simulated data. Mass flow predictions were to within 2% of measured data, and the timings and magnitudes of all major gas dynamic effects were well replicated. The simulation will be further developed in the near future to help with the optimisation of exhaust and inlet silencers.

Novel Approach on the Optimisation of Mid-Course Corrections Along Interplanetary Trajectories

NASA Astrophysics Data System (ADS)

Iorfida, Elisabetta; Palmer, Phil; Roberts, Mark

The primer vector theory, firstly proposed by Lawden, defines a set of necessary conditions to characterise whether an impulsive thrust trajectory is optimal with respect to propellant usage, within a two-body problem context. If the conditions are not satisfied, one or more potential intermediate impulses are performed along the transfer arc, in order to lower the overall cost. The method is based on the propagation of the state transition matrix and on the solution of a boundary value problem, which leads to a mathematical and computational complexity.In this paper, a different approach is introduced. It is based on a polar coordinates transformation of the primer vector which allows the decoupling between its in-plane and out-of-plane components. The out-of-plane component is solved analytically while for the in-plane ones a Hamiltonian approximation is made.The novel procedure reduces the mathematical complexity and the computational cost of Lawden's problem and gives also a different perspective about the optimisation of a transfer trajectory.

Statistical optimisation techniques in fatigue signal editing problem

NASA Astrophysics Data System (ADS)

Nopiah, Z. M.; Osman, M. H.; Baharin, N.; Abdullah, S.

2015-02-01

Success in fatigue signal editing is determined by the level of length reduction without compromising statistical constraints. A great reduction rate can be achieved by removing small amplitude cycles from the recorded signal. The long recorded signal sometimes renders the cycle-to-cycle editing process daunting. This has encouraged researchers to focus on the segment-based approach. This paper discusses joint application of the Running Damage Extraction (RDE) technique and single constrained Genetic Algorithm (GA) in fatigue signal editing optimisation.. In the first section, the RDE technique is used to restructure and summarise the fatigue strain. This technique combines the overlapping window and fatigue strain-life models. It is designed to identify and isolate the fatigue events that exist in the variable amplitude strain data into different segments whereby the retention of statistical parameters and the vibration energy are considered. In the second section, the fatigue data editing problem is formulated as a constrained single optimisation problem that can be solved using GA method. The GA produces the shortest edited fatigue signal by selecting appropriate segments from a pool of labelling segments. Challenges arise due to constraints on the segment selection by deviation level over three signal properties, namely cumulative fatigue damage, root mean square and kurtosis values. Experimental results over several case studies show that the idea of solving fatigue signal editing within a framework of optimisation is effective and automatic, and that the GA is robust for constrained segment selection.

Statistical optimisation techniques in fatigue signal editing problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nopiah, Z. M.; Osman, M. H.; Baharin, N.

Success in fatigue signal editing is determined by the level of length reduction without compromising statistical constraints. A great reduction rate can be achieved by removing small amplitude cycles from the recorded signal. The long recorded signal sometimes renders the cycle-to-cycle editing process daunting. This has encouraged researchers to focus on the segment-based approach. This paper discusses joint application of the Running Damage Extraction (RDE) technique and single constrained Genetic Algorithm (GA) in fatigue signal editing optimisation.. In the first section, the RDE technique is used to restructure and summarise the fatigue strain. This technique combines the overlapping window andmore » fatigue strain-life models. It is designed to identify and isolate the fatigue events that exist in the variable amplitude strain data into different segments whereby the retention of statistical parameters and the vibration energy are considered. In the second section, the fatigue data editing problem is formulated as a constrained single optimisation problem that can be solved using GA method. The GA produces the shortest edited fatigue signal by selecting appropriate segments from a pool of labelling segments. Challenges arise due to constraints on the segment selection by deviation level over three signal properties, namely cumulative fatigue damage, root mean square and kurtosis values. Experimental results over several case studies show that the idea of solving fatigue signal editing within a framework of optimisation is effective and automatic, and that the GA is robust for constrained segment selection.« less

Adaptive swarm cluster-based dynamic multi-objective synthetic minority oversampling technique algorithm for tackling binary imbalanced datasets in biomedical data classification.

PubMed

Li, Jinyan; Fong, Simon; Sung, Yunsick; Cho, Kyungeun; Wong, Raymond; Wong, Kelvin K L

2016-01-01

An imbalanced dataset is defined as a training dataset that has imbalanced proportions of data in both interesting and uninteresting classes. Often in biomedical applications, samples from the stimulating class are rare in a population, such as medical anomalies, positive clinical tests, and particular diseases. Although the target samples in the primitive dataset are small in number, the induction of a classification model over such training data leads to poor prediction performance due to insufficient training from the minority class. In this paper, we use a novel class-balancing method named adaptive swarm cluster-based dynamic multi-objective synthetic minority oversampling technique (ASCB_DmSMOTE) to solve this imbalanced dataset problem, which is common in biomedical applications. The proposed method combines under-sampling and over-sampling into a swarm optimisation algorithm. It adaptively selects suitable parameters for the rebalancing algorithm to find the best solution. Compared with the other versions of the SMOTE algorithm, significant improvements, which include higher accuracy and credibility, are observed with ASCB_DmSMOTE. Our proposed method tactfully combines two rebalancing techniques together. It reasonably re-allocates the majority class in the details and dynamically optimises the two parameters of SMOTE to synthesise a reasonable scale of minority class for each clustered sub-imbalanced dataset. The proposed methods ultimately overcome other conventional methods and attains higher credibility with even greater accuracy of the classification model.

Evaluation of a High Throughput Starch Analysis Optimised for Wood

PubMed Central

Bellasio, Chandra; Fini, Alessio; Ferrini, Francesco

2014-01-01

Starch is the most important long-term reserve in trees, and the analysis of starch is therefore useful source of physiological information. Currently published protocols for wood starch analysis impose several limitations, such as long procedures and a neutralization step. The high-throughput standard protocols for starch analysis in food and feed represent a valuable alternative. However, they have not been optimised or tested with woody samples. These have particular chemical and structural characteristics, including the presence of interfering secondary metabolites, low reactivity of starch, and low starch content. In this study, a standard method for starch analysis used for food and feed (AOAC standard method 996.11) was optimised to improve precision and accuracy for the analysis of starch in wood. Key modifications were introduced in the digestion conditions and in the glucose assay. The optimised protocol was then evaluated through 430 starch analyses of standards at known starch content, matrix polysaccharides, and wood collected from three organs (roots, twigs, mature wood) of four species (coniferous and flowering plants). The optimised protocol proved to be remarkably precise and accurate (3%), suitable for a high throughput routine analysis (35 samples a day) of specimens with a starch content between 40 mg and 21 µg. Samples may include lignified organs of coniferous and flowering plants and non-lignified organs, such as leaves, fruits and rhizomes. PMID:24523863

Sampling Frequency Optimisation and Nonlinear Distortion Mitigation in Subsampling Receiver

NASA Astrophysics Data System (ADS)

Castanheira, Pedro Xavier Melo Fernandes

Subsampling receivers utilise the subsampling method to down convert signals from radio frequency (RF) to a lower frequency location. Multiple signals can also be down converted using the subsampling receiver, but using the incorrect subsampling frequency could result in signals aliasing one another after down conversion. The existing method for subsampling multiband signals focused on down converting all the signals without any aliasing between the signals. The case considered initially was a dual band signal, and then it was further extended to a more general multiband case. In this thesis, a new method is proposed with the assumption that only one signal is needed to not overlap the other multiband signals that are down converted at the same time. The proposed method will introduce unique formulas using the said assumption to calculate the valid subsampling frequencies, ensuring that the target signal is not aliased by the other signals. Simulation results show that the proposed method will provide lower valid subsampling frequencies for down conversion compared to the existing methods.

An automated technique to stage lower third molar development on panoramic radiographs for age estimation: a pilot study.

PubMed

De Tobel, J; Radesh, P; Vandermeulen, D; Thevissen, P W

2017-12-01

Automated methods to evaluate growth of hand and wrist bones on radiographs and magnetic resonance imaging have been developed. They can be applied to estimate age in children and subadults. Automated methods require the software to (1) recognise the region of interest in the image(s), (2) evaluate the degree of development and (3) correlate this to the age of the subject based on a reference population. For age estimation based on third molars an automated method for step (1) has been presented for 3D magnetic resonance imaging and is currently being optimised (Unterpirker et al. 2015). To develop an automated method for step (2) based on lower third molars on panoramic radiographs. A modified Demirjian staging technique including ten developmental stages was developed. Twenty panoramic radiographs per stage per gender were retrospectively selected for FDI element 38. Two observers decided in consensus about the stages. When necessary, a third observer acted as a referee to establish the reference stage for the considered third molar. This set of radiographs was used as training data for machine learning algorithms for automated staging. First, image contrast settings were optimised to evaluate the third molar of interest and a rectangular bounding box was placed around it in a standardised way using Adobe Photoshop CC 2017 software. This bounding box indicated the region of interest for the next step. Second, several machine learning algorithms available in MATLAB R2017a software were applied for automated stage recognition. Third, the classification performance was evaluated in a 5-fold cross-validation scenario, using different validation metrics (accuracy, Rank-N recognition rate, mean absolute difference, linear kappa coefficient). Transfer Learning as a type of Deep Learning Convolutional Neural Network approach outperformed all other tested approaches. Mean accuracy equalled 0.51, mean absolute difference was 0.6 stages and mean linearly weighted kappa was 0.82. The overall performance of the presented automated pilot technique to stage lower third molar development on panoramic radiographs was similar to staging by human observers. It will be further optimised in future research, since it represents a necessary step to achieve a fully automated dental age estimation method, which to date is not available.

Rotational degree-of-freedom synthesis: An optimised finite difference method for non-exact data

NASA Astrophysics Data System (ADS)

Gibbons, T. J.; Öztürk, E.; Sims, N. D.

2018-01-01

Measuring the rotational dynamic behaviour of a structure is important for many areas of dynamics such as passive vibration control, acoustics, and model updating. Specialist and dedicated equipment is often needed, unless the rotational degree-of-freedom is synthesised based upon translational data. However, this involves numerically differentiating the translational mode shapes to approximate the rotational modes, for example using a finite difference algorithm. A key challenge with this approach is choosing the measurement spacing between the data points, an issue which has often been overlooked in the published literature. The present contribution will for the first time prove that the use of a finite difference approach can be unstable when using non-exact measured data and a small measurement spacing, for beam-like structures. Then, a generalised analytical error analysis is used to propose an optimised measurement spacing, which balances the numerical error of the finite difference equation with the propagation error from the perturbed data. The approach is demonstrated using both numerical and experimental investigations. It is shown that by obtaining a small number of test measurements it is possible to optimise the measurement accuracy, without any further assumptions on the boundary conditions of the structure.

Prediction of road traffic death rate using neural networks optimised by genetic algorithm.

PubMed

Jafari, Seyed Ali; Jahandideh, Sepideh; Jahandideh, Mina; Asadabadi, Ebrahim Barzegari

2015-01-01

Road traffic injuries (RTIs) are realised as a main cause of public health problems at global, regional and national levels. Therefore, prediction of road traffic death rate will be helpful in its management. Based on this fact, we used an artificial neural network model optimised through Genetic algorithm to predict mortality. In this study, a five-fold cross-validation procedure on a data set containing total of 178 countries was used to verify the performance of models. The best-fit model was selected according to the root mean square errors (RMSE). Genetic algorithm, as a powerful model which has not been introduced in prediction of mortality to this extent in previous studies, showed high performance. The lowest RMSE obtained was 0.0808. Such satisfactory results could be attributed to the use of Genetic algorithm as a powerful optimiser which selects the best input feature set to be fed into the neural networks. Seven factors have been known as the most effective factors on the road traffic mortality rate by high accuracy. The gained results displayed that our model is very promising and may play a useful role in developing a better method for assessing the influence of road traffic mortality risk factors.

Dead-time optimisation with reducing voltage distortion for nine-switch inverter

NASA Astrophysics Data System (ADS)

Alizadeh Pahlavani, Mohamadreza; Sanatgar Hasankiadeh, Meisam; Bali Lashak, Aref

2018-03-01

Nine-switch inverter with two sets of three-phase outputs is an improved topology proposed in place of the 12-switch back-to-back converters and has therefore attracted much attention in recent years. This inverter can be used with two conventional pulse width modulation approaches: different frequency and the constant frequency. One disadvantage of using this modulation method is the possibility of short-circuits in the legs (shoot-through), which decreases the reliability of converter and system. This paper presents a new modulation technique, in which switching pulses of nine-switch inverter are produced by not only the original carrier signals but also through two auxiliary carrier signals. In this method, adjustable three-phase voltages are produced in the inverter's terminals, and so there is no possibility of any shoot-through in the inverter's legs. The suggested reliable modulation approach does not rely on any information about the load polarity, as switching is performed by a simple and reliable algorithm. The result is the considerably better waveform quality of the output voltages in comparison with other methods. To verify the analysis, an experimental platform based on DSP is built. The simulation and experimental results are given to demonstrate the effectiveness and feasibility of this new approach.

Person-centred medicines optimisation policy in England: an agenda for research on polypharmacy.

PubMed

Heaton, Janet; Britten, Nicky; Krska, Janet; Reeve, Joanne

2017-01-01

Aim To examine how patient perspectives and person-centred care values have been represented in documents on medicines optimisation policy in England. There has been growing support in England for a policy of medicines optimisation as a response to the rise of problematic polypharmacy. Conceptually, medicines optimisation differs from the medicines management model of prescribing in being based around the patient rather than processes and systems. This critical examination of current official and independent policy documents questions how central the patient is in them and whether relevant evidence has been utilised in their development. A documentary analysis of reports on medicines optimisation published by the Royal Pharmaceutical Society (RPS), The King's Fund and National Institute for Health and Social Care Excellence since 2013. The analysis draws on a non-systematic review of research on patient experiences of using medicines. Findings The reports varied in their inclusion of patient perspectives and person-centred care values, and in the extent to which they drew on evidence from research on patients' experiences of polypharmacy and medicines use. In the RPS report, medicines optimisation is represented as being a 'step change' from medicines management, in contrast to the other documents which suggest that it is facilitated by the systems and processes that comprise the latter model. Only The King's Fund report considered evidence from qualitative studies of people's use of medicines. However, these studies are not without their limitations. We suggest five ways in which researchers could improve this evidence base and so inform the development of future policy: by facilitating reviews of existing research; conducting studies of patient experiences of polypharmacy and multimorbidity; evaluating medicines optimisation interventions; making better use of relevant theories, concepts and tools; and improving patient and public involvement in research and in guideline development.

Development and optimization of a wildfire plume rise model based on remote sensing data inputs - Part 2

NASA Astrophysics Data System (ADS)

Paugam, R.; Wooster, M.; Atherton, J.; Freitas, S. R.; Schultz, M. G.; Kaiser, J. W.

2015-03-01

Biomass burning is one of a relatively few natural processes that can inject globally significant quantities of gases and aerosols into the atmosphere at altitudes well above the planetary boundary layer, in some cases at heights in excess of 10 km. The "injection height" of biomass burning emissions is therefore an important parameter to understand when considering the characteristics of the smoke plumes emanating from landscape scale fires, and in particular when attempting to model their atmospheric transport. Here we further extend the formulations used within a popular 1D plume rise model, widely used for the estimation of landscape scale fire smoke plume injection height, and develop and optimise the model both so that it can run with an increased set of remotely sensed observations. The model is well suited for application in atmospheric Chemistry Transport Models (CTMs) aimed at understanding smoke plume downstream impacts, and whilst a number of wildfire emission inventories are available for use in such CTMs, few include information on plume injection height. Since CTM resolutions are typically too spatially coarse to capture the vertical transport induced by the heat released from landscape scale fires, approaches to estimate the emissions injection height are typically based on parametrizations. Our extensions of the existing 1D plume rise model takes into account the impact of atmospheric stability and latent heat on the plume up-draft, driving it with new information on active fire area and fire radiative power (FRP) retrieved from MODIS satellite Earth Observation (EO) data, alongside ECMWF atmospheric profile information. We extend the model by adding an equation for mass conservation and a new entrainment scheme, and optimise the values of the newly added parameters based on comparison to injection heights derived from smoke plume height retrievals made using the MISR EO sensor. Our parameter optimisation procedure is based on a twofold approach using sequentially a Simulating Annealing algorithm and a Markov chain Monte Carlo uncertainty test, and to try to ensure the appropriate convergence on suitable parameter values we use a training dataset consisting of only fires where a number of specific quality criteria are met, including local ambient wind shear limits derived from the ECMWF and MISR data, and "steady state" plumes and fires showing only relatively small changes between consecutive MODIS observations. Using our optimised plume rise model (PRMv2) with information from all MODIS-detected active fires detected in 2003 over North America, with outputs gridded to a 0.1° horizontal and 500 m vertical resolution mesh, we are able to derive wildfire injection height distributions whose maxima extend to the type of higher altitudes seen in actual observation-based wildfire plume datasets than are those derived either via the original plume model or any other parametrization tested herein. We also find our model to be the only one tested that more correctly simulates the very high plume (6 to 8 km a.s.l.), created by a large fire in Alberta (Canada) on the 17 August 2003, though even our approach does not reach the stratosphere as the real plume is expected to have done. Our results lead us to believe that our PRMv2 approach to modelling the injection height of wildfire plumes is a strong candidate for inclusion into CTMs aiming to represent this process, but we note that significant advances in the spatio-temporal resolutions of the data required to feed the model will also very likely bring key improvements in our ability to more accurately represent such phenomena, and that there remain challenges to the detailed validation of such simulations due to the relative sparseness of plume height observations and their currently rather limited temporal coverage which are not necessarily well matched to when fires are most active (MISR being confined to morning observations for example).

Incorporating GIS data into an agent-based model to support planning policy making for the development of creative industries

NASA Astrophysics Data System (ADS)

Liu, Helin; Silva, Elisabete A.; Wang, Qian

2016-07-01

This paper presents an extension to the agent-based model "Creative Industries Development-Urban Spatial Structure Transformation" by incorporating GIS data. Three agent classes, creative firms, creative workers and urban government, are considered in the model, and the spatial environment represents a set of GIS data layers (i.e. road network, key housing areas, land use). With the goal to facilitate urban policy makers to draw up policies locally and optimise the land use assignment in order to support the development of creative industries, the improved model exhibited its capacity to assist the policy makers conducting experiments and simulating different policy scenarios to see the corresponding dynamics of the spatial distributions of creative firms and creative workers across time within a city/district. The spatiotemporal graphs and maps record the simulation results and can be used as a reference by the policy makers to adjust land use plans adaptively at different stages of the creative industries' development process.

Comprehensive ecosystem model-experiment synthesis using multiple datasets at two temperate forest free-air CO2 enrichment experiments: model performance and compensating biases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walker, Anthony P; Hanson, Paul J; DeKauwe, Martin G

2014-01-01

Free Air CO2 Enrichment (FACE) experiments provide a remarkable wealth of data to test the sensitivities of terrestrial ecosystem models (TEMs). In this study, a broad set of 11 TEMs were compared to 22 years of data from two contrasting FACE experiments in temperate forests of the south eastern US the evergreen Duke Forest and the deciduous Oak Ridge forest. We evaluated the models' ability to reproduce observed net primary productivity (NPP), transpiration and Leaf Area index (LAI) in ambient CO2 treatments. Encouragingly, many models simulated annual NPP and transpiration within observed uncertainty. Daily transpiration model errors were often relatedmore » to errors in leaf area phenology and peak LAI. Our analysis demonstrates that the simulation of LAI often drives the simulation of transpiration and hence there is a need to adopt the most appropriate of hypothesis driven methods to simulate and predict LAI. Of the three competing hypotheses determining peak LAI (1) optimisation to maximise carbon export, (2) increasing SLA with canopy depth and (3) the pipe model the pipe model produced LAI closest to the observations. Modelled phenology was either prescribed or based on broader empirical calibrations to climate. In some cases, simulation accuracy was achieved through compensating biases in component variables. For example, NPP accuracy was sometimes achieved with counter-balancing biases in nitrogen use efficiency and nitrogen uptake. Combined analysis of parallel measurements aides the identification of offsetting biases; without which over-confidence in model abilities to predict ecosystem function may emerge, potentially leading to erroneous predictions of change under future climates.« less

Evolving optimised decision rules for intrusion detection using particle swarm paradigm

NASA Astrophysics Data System (ADS)

Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

2012-12-01

The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

Cardiac phenotyping in ex vivo murine embryos using microMRI.

PubMed

Cleary, Jon O; Price, Anthony N; Thomas, David L; Scambler, Peter J; Kyriakopoulou, Vanessa; McCue, Karen; Schneider, Jürgen E; Ordidge, Roger J; Lythgoe, Mark F

2009-10-01

Microscopic MRI (microMRI) is an emerging technique for high-throughput phenotyping of transgenic mouse embryos, and is capable of visualising abnormalities in cardiac development. To identify cardiac defects in embryos, we have optimised embryo preparation and MR acquisition parameters to maximise image quality and assess the phenotypic changes in chromodomain helicase DNA-binding protein 7 (Chd7) transgenic mice. microMRI methods rely on tissue penetration with a gadolinium chelate contrast agent to reduce tissue T(1), thus improving signal-to-noise ratio (SNR) in rapid gradient echo sequences. We investigated 15.5 days post coitum (dpc) wild-type CD-1 embryos fixed in gadolinium-diethylene triamine pentaacetic acid (Gd-DTPA) solutions for either 3 days (2 and 4 mM) or 2 weeks (2, 4, 8 and 16 mM). To assess penetration of the contrast agent into heart tissue and enable image contrast simulations, T(1) and T(*) (2) were measured in heart and background agarose. Compared to 3-day, 2-week fixation showed reduced mean T(1) in the heart at both 2 and 4 mM concentrations (p < 0.0001), resulting in calculated signal gains of 23% (2 mM) and 29% (4 mM). Using T(1) and T(*) (2) values from 2-week concentrations, computer simulation of heart and background signal, and ex vivo 3D gradient echo imaging, we demonstrated that 2-week fixed embryos in 8 mM Gd-DTPA in combination with optimised parameters (TE/TR/alpha/number of averages: 9 ms/20 ms/60 degrees /7) produced the largest SNR in the heart (23.2 +/- 1.0) and heart chamber contrast-to-noise ratio (CNR) (27.1 +/- 1.6). These optimised parameters were then applied to an MRI screen of embryos heterozygous for the gene Chd7, implicated in coloboma of the eye, heart defects, atresia of the choanae, retardation of growth, genital/urinary abnormalities, ear abnormalities and deafness (CHARGE) syndrome (a condition partly characterised by cardiovascular birth defects in humans). A ventricular septal defect was readily identified in the screen, consistent with the human phenotype. (c) 2009 John Wiley & Sons, Ltd.

Modelling a hydropower plant with reservoir with the micropower optimisation model (HOMER)

NASA Astrophysics Data System (ADS)

Canales, Fausto A.; Beluco, Alexandre; Mendes, Carlos André B.

2017-08-01

Hydropower with water accumulation is an interesting option to consider in hybrid systems, because it helps dealing with the intermittence characteristics of renewable energy resources. The software HOMER (version Legacy) is extensively used in research works related to these systems, but it does not include a specific option for modelling hydro with reservoir. This paper describes a method for modelling a hydropower plant with reservoir with HOMER by adapting an existing procedure used for modelling pumped storage. An example with two scenarios in southern Brazil is presented for illustrating and validating the method explained in this paper. The results validate the method by showing a direct correspondence between an equivalent battery and the reservoir. The refill of the reservoir, its power output as a function of the flow rate and installed hydropower capacity are effectively simulated, indicating an adequate representation of a hydropower plant with reservoir is possible with HOMER.

Characterisation and optimisation of a method for the detection and quantification of atmospherically relevant carbonyl compounds in aqueous medium

NASA Astrophysics Data System (ADS)

Rodigast, M.; Mutzel, A.; Iinuma, Y.; Haferkorn, S.; Herrmann, H.

2015-01-01

Carbonyl compounds are ubiquitous in the atmosphere and either emitted primarily from anthropogenic and biogenic sources or they are produced secondarily from the oxidation of volatile organic compounds (VOC). Despite a number of studies about the quantification of carbonyl compounds a comprehensive description of optimised methods is scarce for the quantification of atmospherically relevant carbonyl compounds. Thus a method was systematically characterised and improved to quantify carbonyl compounds. Quantification with the present method can be carried out for each carbonyl compound sampled in the aqueous phase regardless of their source. The method optimisation was conducted for seven atmospherically relevant carbonyl compounds including acrolein, benzaldehyde, glyoxal, methyl glyoxal, methacrolein, methyl vinyl ketone and 2,3-butanedione. O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine hydrochloride (PFBHA) was used as derivatisation reagent and the formed oximes were detected by gas chromatography/mass spectrometry (GC/MS). The main advantage of the improved method presented in this study is the low detection limit in the range of 0.01 and 0.17 μmol L-1 depending on carbonyl compounds. Furthermore best results were found for extraction with dichloromethane for 30 min followed by derivatisation with PFBHA for 24 h with 0.43 mg mL-1 PFBHA at a pH value of 3. The optimised method was evaluated in the present study by the OH radical initiated oxidation of 3-methylbutanone in the aqueous phase. Methyl glyoxal and 2,3-butanedione were found to be oxidation products in the samples with a yield of 2% for methyl glyoxal and 14% for 2,3-butanedione.

Robust optimisation-based microgrid scheduling with islanding constraints

DOE PAGES

Liu, Guodong; Starke, Michael; Xiao, Bailu; ...

2017-02-17

This paper proposes a robust optimization based optimal scheduling model for microgrid operation considering constraints of islanding capability. Our objective is to minimize the total operation cost, including generation cost and spinning reserve cost of local resources as well as purchasing cost of energy from the main grid. In order to ensure the resiliency of a microgrid and improve the reliability of the local electricity supply, the microgrid is required to maintain enough spinning reserve (both up and down) to meet local demand and accommodate local renewable generation when the supply of power from the main grid is interrupted suddenly,more » i.e., microgrid transitions from grid-connected into islanded mode. Prevailing operational uncertainties in renewable energy resources and load are considered and captured using a robust optimization method. With proper robust level, the solution of the proposed scheduling model ensures successful islanding of the microgrid with minimum load curtailment and guarantees robustness against all possible realizations of the modeled operational uncertainties. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator and a battery demonstrate the effectiveness of the proposed scheduling model.« less

Locating helicopter emergency medical service bases to optimise population coverage versus average response time.

PubMed

Garner, Alan A; van den Berg, Pieter L

2017-10-16

New South Wales (NSW), Australia has a network of multirole retrieval physician staffed helicopter emergency medical services (HEMS) with seven bases servicing a jurisdiction with population concentrated along the eastern seaboard. The aim of this study was to estimate optimal HEMS base locations within NSW using advanced mathematical modelling techniques. We used high resolution census population data for NSW from 2011 which divides the state into areas containing 200-800 people. Optimal HEMS base locations were estimated using the maximal covering location problem facility location optimization model and the average response time model, exploring the number of bases needed to cover various fractions of the population for a 45 min response time threshold or minimizing the overall average response time to all persons, both in green field scenarios and conditioning on the current base structure. We also developed a hybrid mathematical model where average response time was optimised based on minimum population coverage thresholds. Seven bases could cover 98% of the population within 45mins when optimised for coverage or reach the entire population of the state within an average of 21mins if optimised for response time. Given the existing bases, adding two bases could either increase the 45 min coverage from 91% to 97% or decrease the average response time from 21mins to 19mins. Adding a single specialist prehospital rapid response HEMS to the area of greatest population concentration decreased the average state wide response time by 4mins. The optimum seven base hybrid model that was able to cover 97.75% of the population within 45mins, and all of the population in an average response time of 18 mins included the rapid response HEMS model. HEMS base locations can be optimised based on either percentage of the population covered, or average response time to the entire population. We have also demonstrated a hybrid technique that optimizes response time for a given number of bases and minimum defined threshold of population coverage. Addition of specialized rapid response HEMS services to a system of multirole retrieval HEMS may reduce overall average response times by improving access in large urban areas.

A simple method for low-contrast detectability, image quality and dose optimisation with CT iterative reconstruction algorithms and model observers.

PubMed

Bellesi, Luca; Wyttenbach, Rolf; Gaudino, Diego; Colleoni, Paolo; Pupillo, Francesco; Carrara, Mauro; Braghetti, Antonio; Puligheddu, Carla; Presilla, Stefano

2017-01-01

The aim of this work was to evaluate detection of low-contrast objects and image quality in computed tomography (CT) phantom images acquired at different tube loadings (i.e. mAs) and reconstructed with different algorithms, in order to find appropriate settings to reduce the dose to the patient without any image detriment. Images of supraslice low-contrast objects of a CT phantom were acquired using different mAs values. Images were reconstructed using filtered back projection (FBP), hybrid and iterative model-based methods. Image quality parameters were evaluated in terms of modulation transfer function; noise, and uniformity using two software resources. For the definition of low-contrast detectability, studies based on both human (i.e. four-alternative forced-choice test) and model observers were performed across the various images. Compared to FBP, image quality parameters were improved by using iterative reconstruction (IR) algorithms. In particular, IR model-based methods provided a 60% noise reduction and a 70% dose reduction, preserving image quality and low-contrast detectability for human radiological evaluation. According to the model observer, the diameters of the minimum detectable detail were around 2 mm (up to 100 mAs). Below 100 mAs, the model observer was unable to provide a result. IR methods improve CT protocol quality, providing a potential dose reduction while maintaining a good image detectability. Model observer can in principle be useful to assist human performance in CT low-contrast detection tasks and in dose optimisation.

The Thistle Field - Analysis of its past performance and optimisation of its future development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bayat, M.G.; Tehrani, D.H.

1985-01-01

The Thistle Field geology and its reservoir performance over the past six years have been reviewed. The latest reservoir simulation study of the field, covering the performance history-matching, and the conclusions of various prediction cases are reported. The special features of PORES, Britoil in-house 3D 3-phase fully implicit numerical simulator and its modeling aids as applied to the Thistle Field are presented.

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

NASA Astrophysics Data System (ADS)

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.

FPGA-based RF interference reduction techniques for simultaneous PET–MRI

PubMed Central

Gebhardt, P; Wehner, J; Weissler, B; Botnar, R; Marsden, P K; Schulz, V

2016-01-01

Abstract The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET–MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling–decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion IID PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field distribution, followed by MRI noise and SNR scans performed with an operating PET module using different clock frequencies and phase patterns. The methods were implemented via firmware design changes without any hardware modifications. This introduces new means of flexibility by enabling adaptive RF interference reduction optimisations in the field, e.g. when using a PET insert with different MRI systems or when different MRI RF coil types are to be operated with the same PET detector. PMID:27049898

FPGA-based RF interference reduction techniques for simultaneous PET-MRI.

PubMed

Gebhardt, P; Wehner, J; Weissler, B; Botnar, R; Marsden, P K; Schulz, V

2016-05-07

The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET-MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling-decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion II (D) PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field distribution, followed by MRI noise and SNR scans performed with an operating PET module using different clock frequencies and phase patterns. The methods were implemented via firmware design changes without any hardware modifications. This introduces new means of flexibility by enabling adaptive RF interference reduction optimisations in the field, e.g. when using a PET insert with different MRI systems or when different MRI RF coil types are to be operated with the same PET detector.

FPGA-based RF interference reduction techniques for simultaneous PET-MRI

NASA Astrophysics Data System (ADS)

Gebhardt, P.; Wehner, J.; Weissler, B.; Botnar, R.; Marsden, P. K.; Schulz, V.

2016-05-01

The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET-MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling-decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion II D PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field distribution, followed by MRI noise and SNR scans performed with an operating PET module using different clock frequencies and phase patterns. The methods were implemented via firmware design changes without any hardware modifications. This introduces new means of flexibility by enabling adaptive RF interference reduction optimisations in the field, e.g. when using a PET insert with different MRI systems or when different MRI RF coil types are to be operated with the same PET detector.

A Refrigerated Web Camera for Photogrammetric Video Measurement inside Biomass Boilers and Combustion Analysis

PubMed Central

Porteiro, Jacobo; Riveiro, Belén; Granada, Enrique; Armesto, Julia; Eguía, Pablo; Collazo, Joaquín

2011-01-01

This paper describes a prototype instrumentation system for photogrammetric measuring of bed and ash layers, as well as for flying particle detection and pursuit using a single device (CCD) web camera. The system was designed to obtain images of the combustion process in the interior of a domestic boiler. It includes a cooling system, needed because of the high temperatures in the combustion chamber of the boiler. The cooling system was designed using CFD simulations to ensure effectiveness. This method allows more complete and real-time monitoring of the combustion process taking place inside a boiler. The information gained from this system may facilitate the optimisation of boiler processes. PMID:22319349

Reconstruction of hadronic decay products of tau leptons with the ATLAS experiment

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2016-05-25

This document presents a new method of reconstructing the individual charged and neutral hadrons in tau decays with the ATLAS detector. The reconstructed hadrons are used to classify the decay mode and to calculate the visible four-momentum of reconstructed tau candidates, significantly improving the resolution with respect to the calibration in the existing tau reconstruction. The performance of the reconstruction algorithm is optimised and evaluated using simulation and validated using samples of Z → ττ and Z(→ μμ)+jets events selected from proton–proton collisions at a centre-of-mass energy √s = 8 TeV, corresponding to an integrated luminosity of 5 fb -1.

A refrigerated web camera for photogrammetric video measurement inside biomass boilers and combustion analysis.

PubMed

Porteiro, Jacobo; Riveiro, Belén; Granada, Enrique; Armesto, Julia; Eguía, Pablo; Collazo, Joaquín

2011-01-01

This paper describes a prototype instrumentation system for photogrammetric measuring of bed and ash layers, as well as for flying particle detection and pursuit using a single device (CCD) web camera. The system was designed to obtain images of the combustion process in the interior of a domestic boiler. It includes a cooling system, needed because of the high temperatures in the combustion chamber of the boiler. The cooling system was designed using CFD simulations to ensure effectiveness. This method allows more complete and real-time monitoring of the combustion process taking place inside a boiler. The information gained from this system may facilitate the optimisation of boiler processes.

Incompressible SPH (ISPH) with fast Poisson solver on a GPU

NASA Astrophysics Data System (ADS)

Chow, Alex D.; Rogers, Benedict D.; Lind, Steven J.; Stansby, Peter K.

2018-05-01

This paper presents a fast incompressible SPH (ISPH) solver implemented to run entirely on a graphics processing unit (GPU) capable of simulating several millions of particles in three dimensions on a single GPU. The ISPH algorithm is implemented by converting the highly optimised open-source weakly-compressible SPH (WCSPH) code DualSPHysics to run ISPH on the GPU, combining it with the open-source linear algebra library ViennaCL for fast solutions of the pressure Poisson equation (PPE). Several challenges are addressed with this research: constructing a PPE matrix every timestep on the GPU for moving particles, optimising the limited GPU memory, and exploiting fast matrix solvers. The ISPH pressure projection algorithm is implemented as 4 separate stages, each with a particle sweep, including an algorithm for the population of the PPE matrix suitable for the GPU, and mixed precision storage methods. An accurate and robust ISPH boundary condition ideal for parallel processing is also established by adapting an existing WCSPH boundary condition for ISPH. A variety of validation cases are presented: an impulsively started plate, incompressible flow around a moving square in a box, and dambreaks (2-D and 3-D) which demonstrate the accuracy, flexibility, and speed of the methodology. Fragmentation of the free surface is shown to influence the performance of matrix preconditioners and therefore the PPE matrix solution time. The Jacobi preconditioner demonstrates robustness and reliability in the presence of fragmented flows. For a dambreak simulation, GPU speed ups demonstrate up to 10-18 times and 1.1-4.5 times compared to single-threaded and 16-threaded CPU run times respectively.

Quantification of furanic compounds in coated deep-fried products simulating normal preparation and consumption: optimisation of HS-SPME analytical conditions by response surface methodology.

PubMed

Pérez-Palacios, T; Petisca, C; Melo, A; Ferreira, I M P L V O

2012-12-01

The validation of a method for the simultaneous quantification of furanic compounds in coated deep-fried samples processed and handled as usually consumed is presented. The deep-fried food was grinded using a device that simulates the mastication, and immediately analysed by headspace solid phase microextraction coupled to gas chromatography-mass spectrometry. Parameters affecting the efficiency of HS-SPME procedure were selected by response surface methodology, using a 2(3) full-factorial central composite design. Optimal conditions were achieved using 2g of sample, 3g of NaCl and 40min of absorption time at 37°C. Consistency between predicted and experimented values was observed and quality parameters of the method were established. As a result, furan, 2-furfural, furfuryl alcohol and 2-pentylfuran were, for the first time, simultaneously detected and quantified (5.59, 0.27, 10.48 and 1.77μgg(-1) sample, respectively) in coated deep-fried fish, contributing to a better understanding of the amounts of these compounds in food. Copyright © 2012 Elsevier Ltd. All rights reserved.

Quench simulations for superconducting elements in the LHC accelerator

NASA Astrophysics Data System (ADS)

Sonnemann, F.; Schmidt, R.

2000-08-01

The design of the protection system for the superconducting elements in an accelerator such as the large Hadron collider (LHC), now under construction at CERN, requires a detailed understanding of the thermo-hydraulic and electrodynamic processes during a quench. A numerical program (SPQR - simulation program for quench research) has been developed to evaluate temperature and voltage distributions during a quench as a function of space and time. The quench process is simulated by approximating the heat balance equation with the finite difference method in presence of variable cooling and powering conditions. The simulation predicts quench propagation along a superconducting cable, forced quenching with heaters, impact of eddy currents induced by a magnetic field change, and heat transfer through an insulation layer into helium, an adjacent conductor or other material. The simulation studies allowed a better understanding of experimental quench data and were used for determining the adequate dimensioning and protection of the highly stabilised superconducting cables for connecting magnets (busbars), optimising the quench heater strip layout for the main magnets, and studying quench back by induced eddy currents in the superconductor. After the introduction of the theoretical approach, some applications of the simulation model for the LHC dipole and corrector magnets are presented and the outcome of the studies is compared with experimental data.

A radiobiology-based inverse treatment planning method for optimisation of permanent l-125 prostate implants in focal brachytherapy

NASA Astrophysics Data System (ADS)

Haworth, Annette; Mears, Christopher; Betts, John M.; Reynolds, Hayley M.; Tack, Guido; Leo, Kevin; Williams, Scott; Ebert, Martin A.

2016-01-01

Treatment plans for ten patients, initially treated with a conventional approach to low dose-rate brachytherapy (LDR, 145 Gy to entire prostate), were compared with plans for the same patients created with an inverse-optimisation planning process utilising a biologically-based objective. The ‘biological optimisation’ considered a non-uniform distribution of tumour cell density through the prostate based on known and expected locations of the tumour. Using dose planning-objectives derived from our previous biological-model validation study, the volume of the urethra receiving 125% of the conventional prescription (145 Gy) was reduced from a median value of 64% to less than 8% whilst maintaining high values of TCP. On average, the number of planned seeds was reduced from 85 to less than 75. The robustness of plans to random seed displacements needs to be carefully considered when using contemporary seed placement techniques. We conclude that an inverse planning approach to LDR treatments, based on a biological objective, has the potential to maintain high rates of tumour control whilst minimising dose to healthy tissue. In future, the radiobiological model will be informed using multi-parametric MRI to provide a personalised medicine approach.

Apparent resistivity for transient electromagnetic induction logging and its correction in radial layer identification

NASA Astrophysics Data System (ADS)

Meng, Qingxin; Hu, Xiangyun; Pan, Heping; Xi, Yufei

2018-04-01

We propose an algorithm for calculating all-time apparent resistivity from transient electromagnetic induction logging. The algorithm is based on the whole-space transient electric field expression of the uniform model and Halley's optimisation. In trial calculations for uniform models, the all-time algorithm is shown to have high accuracy. We use the finite-difference time-domain method to simulate the transient electromagnetic field in radial two-layer models without wall rock and convert the simulation results to apparent resistivity using the all-time algorithm. The time-varying apparent resistivity reflects the radially layered geoelectrical structure of the models and the apparent resistivity of the earliest time channel follows the true resistivity of the inner layer; however, the apparent resistivity at larger times reflects the comprehensive electrical characteristics of the inner and outer layers. To accurately identify the outer layer resistivity based on the series relationship model of the layered resistance, the apparent resistivity and diffusion depth of the different time channels are approximately replaced by related model parameters; that is, we propose an apparent resistivity correction algorithm. By correcting the time-varying apparent resistivity of radial two-layer models, we show that the correction results reflect the radially layered electrical structure and the corrected resistivities of the larger time channels follow the outer layer resistivity. The transient electromagnetic fields of radially layered models with wall rock are simulated to obtain the 2D time-varying profiles of the apparent resistivity and corrections. The results suggest that the time-varying apparent resistivity and correction results reflect the vertical and radial geoelectrical structures. For models with small wall-rock effect, the correction removes the effect of the low-resistance inner layer on the apparent resistivity of the larger time channels.

Characterisation and optimisation of a sample preparation method for the detection and quantification of atmospherically relevant carbonyl compounds in aqueous medium

NASA Astrophysics Data System (ADS)

Rodigast, M.; Mutzel, A.; Iinuma, Y.; Haferkorn, S.; Herrmann, H.

2015-06-01

Carbonyl compounds are ubiquitous in the atmosphere and either emitted primarily from anthropogenic and biogenic sources or they are produced secondarily from the oxidation of volatile organic compounds. Despite a number of studies about the quantification of carbonyl compounds a comprehensive description of optimised methods is scarce for the quantification of atmospherically relevant carbonyl compounds. The method optimisation was conducted for seven atmospherically relevant carbonyl compounds including acrolein, benzaldehyde, glyoxal, methyl glyoxal, methacrolein, methyl vinyl ketone and 2,3-butanedione. O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine hydrochloride (PFBHA) was used as derivatisation reagent and the formed oximes were detected by gas chromatography/mass spectrometry (GC/MS). With the present method quantification can be carried out for each carbonyl compound originating from fog, cloud and rain or sampled from the gas- and particle phase in water. Detection limits between 0.01 and 0.17 μmol L-1 were found, depending on carbonyl compounds. Furthermore, best results were found for the derivatisation with a PFBHA concentration of 0.43 mg mL-1 for 24 h followed by a subsequent extraction with dichloromethane for 30 min at pH = 1. The optimised method was evaluated in the present study by the OH radical initiated oxidation of 3-methylbutanone in the aqueous phase. Methyl glyoxal and 2,3-butanedione were found to be oxidation products in the samples with a yield of 2% for methyl glyoxal and 14% for 2,3-butanedione after a reaction time of 5 h.

Investigation of power and frequency for 3D conformal MRI-controlled transurethral ultrasound therapy with a dual frequency multi-element transducer.

PubMed

N'djin, William Apoutou; Burtnyk, Mathieu; Bronskill, Michael; Chopra, Rajiv

2012-01-01

Transurethral ultrasound therapy uses real-time magnetic resonance (MR) temperature feedback to enable the 3D control of thermal therapy accurately in a region within the prostate. Previous canine studies showed the feasibility of this method in vivo. The aim of this study was to reduce the procedure time, while maintaining targeting accuracy, by investigating new combinations of treatment parameters. Simulations and validation experiments in gel phantoms were used, with a collection of nine 3D realistic target prostate boundaries obtained from previous preclinical studies, where multi-slice MR images were acquired with the transurethral device in place. Acoustic power and rotation rate were varied based on temperature feedback at the prostate boundary. Maximum acoustic power and rotation rate were optimised interdependently, as a function of prostate radius and transducer operating frequency. The concept of dual frequency transducers was studied, using the fundamental frequency or the third harmonic component depending on the prostate radius. Numerical modelling enabled assessment of the effects of several acoustic parameters on treatment outcomes. The range of treatable prostate radii extended with increasing power, and tended to narrow with decreasing frequency. Reducing the frequency from 8 MHz to 4 MHz or increasing the surface acoustic power from 10 to 20 W/cm(2) led to treatment times shorter by up to 50% under appropriate conditions. A dual frequency configuration of 4/12 MHz with 20 W/cm(2) ultrasound intensity exposure can treat entire prostates up to 40 cm(3) in volume within 30 min. The interdependence between power and frequency may, however, require integrating multi-parametric functions in the controller for future optimisations.

Control fast or control smart: When should invading pathogens be controlled?

PubMed

Thompson, Robin N; Gilligan, Christopher A; Cunniffe, Nik J

2018-02-01

The intuitive response to an invading pathogen is to start disease management as rapidly as possible, since this would be expected to minimise the future impacts of disease. However, since more spread data become available as an outbreak unfolds, processes underpinning pathogen transmission can almost always be characterised more precisely later in epidemics. This allows the future progression of any outbreak to be forecast more accurately, and so enables control interventions to be targeted more precisely. There is also the chance that the outbreak might die out without any intervention whatsoever, making prophylactic control unnecessary. Optimal decision-making involves continuously balancing these potential benefits of waiting against the possible costs of further spread. We introduce a generic, extensible data-driven algorithm based on parameter estimation and outbreak simulation for making decisions in real-time concerning when and how to control an invading pathogen. The Control Smart Algorithm (CSA) resolves the trade-off between the competing advantages of controlling as soon as possible and controlling later when more information has become available. We show-using a generic mathematical model representing the transmission of a pathogen of agricultural animals or plants through a population of farms or fields-how the CSA allows the timing and level of deployment of vaccination or chemical control to be optimised. In particular, the algorithm outperforms simpler strategies such as intervening when the outbreak size reaches a pre-specified threshold, or controlling when the outbreak has persisted for a threshold length of time. This remains the case even if the simpler methods are fully optimised in advance. Our work highlights the potential benefits of giving careful consideration to the question of when to start disease management during emerging outbreaks, and provides a concrete framework to allow policy-makers to make this decision.

Performance evaluation of a smart buffer control at a wastewater treatment plant.

PubMed

van Daal-Rombouts, P; Benedetti, L; de Jonge, J; Weijers, S; Langeveld, J

2017-11-15

Real time control (RTC) is increasingly seen as a viable method to optimise the functioning of wastewater systems. Model exercises and case studies reported in literature claim a positive impact of RTC based on results without uncertainty analysis and flawed evaluation periods. This paper describes two integrated RTC strategies at the wastewater treatment plant (WWTP) Eindhoven, the Netherlands, that aim to improve the use of the available tanks at the WWTP and storage in the contributing catchments to reduce the impact on the receiving water. For the first time it is demonstrated that a significant improvement can be achieved through the application of RTC in practice. The Storm Tank Control is evaluated based on measurements and reduces the number of storm water settling tank discharges by 44% and the discharged volume by an estimated 33%, decreasing dissolved oxygen depletion in the river. The Primary Clarifier Control is evaluated based on model simulations. The maximum event NH4 concentration in the effluent reduced on average 19% for large events, while the load reduced 20%. For all 31 events the reductions are 11 and 4% respectively. Reductions are significant taking uncertainties into account, while using representative evaluation periods. Copyright © 2017 Elsevier Ltd. All rights reserved.

The use of genomic coancestry matrices in the optimisation of contributions to maintain genetic diversity at specific regions of the genome.

PubMed

Gómez-Romano, Fernando; Villanueva, Beatriz; Fernández, Jesús; Woolliams, John A; Pong-Wong, Ricardo

2016-01-13

Optimal contribution methods have proved to be very efficient for controlling the rates at which coancestry and inbreeding increase and therefore, for maintaining genetic diversity. These methods have usually relied on pedigree information for estimating genetic relationships between animals. However, with the large amount of genomic information now available such as high-density single nucleotide polymorphism (SNP) chips that contain thousands of SNPs, it becomes possible to calculate more accurate estimates of relationships and to target specific regions in the genome where there is a particular interest in maximising genetic diversity. The objective of this study was to investigate the effectiveness of using genomic coancestry matrices for: (1) minimising the loss of genetic variability at specific genomic regions while restricting the overall loss in the rest of the genome; or (2) maximising the overall genetic diversity while restricting the loss of diversity at specific genomic regions. Our study shows that the use of genomic coancestry was very successful at minimising the loss of diversity and outperformed the use of pedigree-based coancestry (genetic diversity even increased in some scenarios). The results also show that genomic information allows a targeted optimisation to maintain diversity at specific genomic regions, whether they are linked or not. The level of variability maintained increased when the targeted regions were closely linked. However, such targeted management leads to an important loss of diversity in the rest of the genome and, thus, it is necessary to take further actions to constrain this loss. Optimal contribution methods also proved to be effective at restricting the loss of diversity in the rest of the genome, although the resulting rate of coancestry was higher than the constraint imposed. The use of genomic matrices when optimising contributions permits the control of genetic diversity and inbreeding at specific regions of the genome through the minimisation of partial genomic coancestry matrices. The formula used to predict coancestry in the next generation produces biased results and therefore it is necessary to refine the theory of genetic contributions when genomic matrices are used to optimise contributions.

Fox-7 for Insensitive Boosters

DTIC Science & Technology

2010-08-01

cavitation , and therefore nucleation, to occur at each frequency. As well as producing ultrasound at different frequencies, the method of delivery of...processing techniques using ultrasound , designed to optimise FOX-7 crystal size and morphology to improve booster formulations, and results from these...7 booster formulations. Also included are particle processing techniques using ultrasound , designed to optimise FOX-7 crystal size and morphology

Model fitting for small skin permeability data sets: hyperparameter optimisation in Gaussian Process Regression.

PubMed

Ashrafi, Parivash; Sun, Yi; Davey, Neil; Adams, Roderick G; Wilkinson, Simon C; Moss, Gary Patrick

2018-03-01

The aim of this study was to investigate how to improve predictions from Gaussian Process models by optimising the model hyperparameters. Optimisation methods, including Grid Search, Conjugate Gradient, Random Search, Evolutionary Algorithm and Hyper-prior, were evaluated and applied to previously published data. Data sets were also altered in a structured manner to reduce their size, which retained the range, or 'chemical space' of the key descriptors to assess the effect of the data range on model quality. The Hyper-prior Smoothbox kernel results in the best models for the majority of data sets, and they exhibited significantly better performance than benchmark quantitative structure-permeability relationship (QSPR) models. When the data sets were systematically reduced in size, the different optimisation methods generally retained their statistical quality, whereas benchmark QSPR models performed poorly. The design of the data set, and possibly also the approach to validation of the model, is critical in the development of improved models. The size of the data set, if carefully controlled, was not generally a significant factor for these models and that models of excellent statistical quality could be produced from substantially smaller data sets. © 2018 Royal Pharmaceutical Society.

A method for subject-specific modelling and optimisation of the cushioning properties of insole materials used in diabetic footwear.

PubMed

Chatzistergos, Panagiotis E; Naemi, Roozbeh; Chockalingam, Nachiappan

2015-06-01

This study aims to develop a numerical method that can be used to investigate the cushioning properties of different insole materials on a subject-specific basis. Diabetic footwear and orthotic insoles play an important role for the reduction of plantar pressure in people with diabetes (type-2). Despite that, little information exists about their optimum cushioning properties. A new in-vivo measurement based computational procedure was developed which entails the generation of 2D subject-specific finite element models of the heel pad based on ultrasound indentation. These models are used to inverse engineer the material properties of the heel pad and simulate the contact between plantar soft tissue and a flat insole. After its validation this modelling procedure was utilised to investigate the importance of plantar soft tissue stiffness, thickness and loading for the correct selection of insole material. The results indicated that heel pad stiffness and thickness influence plantar pressure but not the optimum insole properties. On the other hand loading appears to significantly influence the optimum insole material properties. These results indicate that parameters that affect the loading of the plantar soft tissues such as body mass or a person's level of physical activity should be carefully considered during insole material selection. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Whole-brain high in-plane resolution fMRI using accelerated EPIK for enhanced characterisation of functional areas at 3T

PubMed Central

Yun, Seong Dae

2017-01-01

The relatively high imaging speed of EPI has led to its widespread use in dynamic MRI studies such as functional MRI. An approach to improve the performance of EPI, EPI with Keyhole (EPIK), has been previously presented and its use in fMRI was verified at 1.5T as well as 3T. The method has been proven to achieve a higher temporal resolution and smaller image distortions when compared to single-shot EPI. Furthermore, the performance of EPIK in the detection of functional signals was shown to be comparable to that of EPI. For these reasons, we were motivated to employ EPIK here for high-resolution imaging. The method was optimised to offer the highest possible in-plane resolution and slice coverage under the given imaging constraints: fixed TR/TE, FOV and acceleration factors for parallel imaging and partial Fourier techniques. The performance of EPIK was evaluated in direct comparison to the optimised protocol obtained from EPI. The two imaging methods were applied to visual fMRI experiments involving sixteen subjects. The results showed that enhanced spatial resolution with a whole-brain coverage was achieved by EPIK (1.00 mm × 1.00 mm; 32 slices) when compared to EPI (1.25 mm × 1.25 mm; 28 slices). As a consequence, enhanced characterisation of functional areas has been demonstrated in EPIK particularly for relatively small brain regions such as the lateral geniculate nucleus (LGN) and superior colliculus (SC); overall, a significantly increased t-value and activation area were observed from EPIK data. Lastly, the use of EPIK for fMRI was validated with the simulation of different types of data reconstruction methods. PMID:28945780

Fault tree analysis for integrated and probabilistic risk analysis of drinking water systems.

PubMed

Lindhe, Andreas; Rosén, Lars; Norberg, Tommy; Bergstedt, Olof

2009-04-01

Drinking water systems are vulnerable and subject to a wide range of risks. To avoid sub-optimisation of risk-reduction options, risk analyses need to include the entire drinking water system, from source to tap. Such an integrated approach demands tools that are able to model interactions between different events. Fault tree analysis is a risk estimation tool with the ability to model interactions between events. Using fault tree analysis on an integrated level, a probabilistic risk analysis of a large drinking water system in Sweden was carried out. The primary aims of the study were: (1) to develop a method for integrated and probabilistic risk analysis of entire drinking water systems; and (2) to evaluate the applicability of Customer Minutes Lost (CML) as a measure of risk. The analysis included situations where no water is delivered to the consumer (quantity failure) and situations where water is delivered but does not comply with water quality standards (quality failure). Hard data as well as expert judgements were used to estimate probabilities of events and uncertainties in the estimates. The calculations were performed using Monte Carlo simulations. CML is shown to be a useful measure of risks associated with drinking water systems. The method presented provides information on risk levels, probabilities of failure, failure rates and downtimes of the system. This information is available for the entire system as well as its different sub-systems. Furthermore, the method enables comparison of the results with performance targets and acceptable levels of risk. The method thus facilitates integrated risk analysis and consequently helps decision-makers to minimise sub-optimisation of risk-reduction options.

Understanding the Models of Community Hospital rehabilitation Activity (MoCHA): a mixed-methods study

PubMed Central

Gladman, John; Buckell, John; Young, John; Smith, Andrew; Hulme, Clare; Saggu, Satti; Godfrey, Mary; Enderby, Pam; Teale, Elizabeth; Longo, Roberto; Gannon, Brenda; Holditch, Claire; Eardley, Heather; Tucker, Helen

2017-01-01

Introduction To understand the variation in performance between community hospitals, our objectives are: to measure the relative performance (cost efficiency) of rehabilitation services in community hospitals; to identify the characteristics of community hospital rehabilitation that optimise performance; to investigate the current impact of community hospital inpatient rehabilitation for older people on secondary care and the potential impact if community hospital rehabilitation was optimised to best practice nationally; to examine the relationship between the configuration of intermediate care and secondary care bed use; and to develop toolkits for commissioners and community hospital providers to optimise performance. Methods and analysis 4 linked studies will be performed. Study 1: cost efficiency modelling will apply econometric techniques to data sets from the National Health Service (NHS) Benchmarking Network surveys of community hospital and intermediate care. This will identify community hospitals' performance and estimate the gap between high and low performers. Analyses will determine the potential impact if the performance of all community hospitals nationally was optimised to best performance, and examine the association between community hospital configuration and secondary care bed use. Study 2: a national community hospital survey gathering detailed cost data and efficiency variables will be performed. Study 3: in-depth case studies of 3 community hospitals, 2 high and 1 low performing, will be undertaken. Case studies will gather routine hospital and local health economy data. Ward culture will be surveyed. Content and delivery of treatment will be observed. Patients and staff will be interviewed. Study 4: co-designed web-based quality improvement toolkits for commissioners and providers will be developed, including indicators of performance and the gap between local and best community hospitals performance. Ethics and dissemination Publications will be in peer-reviewed journals, reports will be distributed through stakeholder organisations. Ethical approval was obtained from the Bradford Research Ethics Committee (reference: 15/YH/0062). PMID:28242766

A neural-network-based exponential H∞ synchronisation for chaotic secure communication via improved genetic algorithm

NASA Astrophysics Data System (ADS)

Hsiao, Feng-Hsiag

2016-10-01

In this study, a novel approach via improved genetic algorithm (IGA)-based fuzzy observer is proposed to realise exponential optimal H∞ synchronisation and secure communication in multiple time-delay chaotic (MTDC) systems. First, an original message is inserted into the MTDC system. Then, a neural-network (NN) model is employed to approximate the MTDC system. Next, a linear differential inclusion (LDI) state-space representation is established for the dynamics of the NN model. Based on this LDI state-space representation, this study proposes a delay-dependent exponential stability criterion derived in terms of Lyapunov's direct method, thus ensuring that the trajectories of the slave system approach those of the master system. Subsequently, the stability condition of this criterion is reformulated into a linear matrix inequality (LMI). Due to GA's random global optimisation search capabilities, the lower and upper bounds of the search space can be set so that the GA will seek better fuzzy observer feedback gains, accelerating feedback gain-based synchronisation via the LMI-based approach. IGA, which exhibits better performance than traditional GA, is used to synthesise a fuzzy observer to not only realise the exponential synchronisation, but also achieve optimal H∞ performance by minimizing the disturbance attenuation level and recovering the transmitted message. Finally, a numerical example with simulations is given in order to demonstrate the effectiveness of our approach.

Dosimetry in x-ray-based breast imaging

PubMed Central

Dance, David R; Sechopoulos, Ioannis

2016-01-01

The estimation of the mean glandular dose to the breast (MGD) for x-ray based imaging modalities forms an essential part of quality control and is needed for risk estimation and for system design and optimisation. This review considers the development of methods for estimating the MGD for mammography, digital breast tomosynthesis (DBT) and dedicated breast CT (DBCT). Almost all of the methodology used employs Monte Carlo calculated conversion factors to relate the measurable quantity, generally the incident air kerma, to the MGD. After a review of the size and composition of the female breast, the various mathematical models used are discussed, with particular emphasis on models for mammography. These range from simple geometrical shapes, to the more recent complex models based on patient DBCT examinations. The possibility of patient-specific dose estimates is considered as well as special diagnostic views and the effect of breast implants. Calculations using the complex models show that the MGD for mammography is overestimated by about 30% when the simple models are used. The design and uses of breast-simulating test phantoms for measuring incident air kerma are outlined and comparisons made between patient and phantom-based dose estimates. The most widely used national and international dosimetry protocols for mammography are based on different simple geometrical models of the breast, and harmonisation of these protocols using more complex breast models is desirable. PMID:27617767

Dosimetry in x-ray-based breast imaging

NASA Astrophysics Data System (ADS)

Dance, David R.; Sechopoulos, Ioannis

2016-10-01

The estimation of the mean glandular dose to the breast (MGD) for x-ray based imaging modalities forms an essential part of quality control and is needed for risk estimation and for system design and optimisation. This review considers the development of methods for estimating the MGD for mammography, digital breast tomosynthesis (DBT) and dedicated breast CT (DBCT). Almost all of the methodology used employs Monte Carlo calculated conversion factors to relate the measurable quantity, generally the incident air kerma, to the MGD. After a review of the size and composition of the female breast, the various mathematical models used are discussed, with particular emphasis on models for mammography. These range from simple geometrical shapes, to the more recent complex models based on patient DBCT examinations. The possibility of patient-specific dose estimates is considered as well as special diagnostic views and the effect of breast implants. Calculations using the complex models show that the MGD for mammography is overestimated by about 30% when the simple models are used. The design and uses of breast-simulating test phantoms for measuring incident air kerma are outlined and comparisons made between patient and phantom-based dose estimates. The most widely used national and international dosimetry protocols for mammography are based on different simple geometrical models of the breast, and harmonisation of these protocols using more complex breast models is desirable.

Determination of sulfur dioxide in wine using headspace gas chromatography and electron capture detection.

PubMed

Aberl, A; Coelhan, M

2013-01-01

Sulfites are routinely added as preservatives and antioxidants in wine production. By law, the total sulfur dioxide content in wine is restricted and therefore must be monitored. Currently, the method of choice for determining the total content of sulfur dioxide in wine is the optimised Monier-Williams method, which is time consuming and laborious. The headspace gas chromatographic method described in this study offers a fast and reliable alternative method for the detection and quantification of the sulfur dioxide content in wine. The analysis was performed using an automatic headspace injection sampler, coupled with a gas chromatograph and an electron capture detector. The method is based on the formation of gaseous sulfur dioxide subsequent to acidification and heating of the sample. In addition to free sulfur dioxide, reversibly bound sulfur dioxide in carbonyl compounds, such as acetaldehyde, was also measured with this method. A total of 20 wine samples produced using diverse grape varieties and vintages of varied provenance were analysed using the new method. For reference and comparison purposes, 10 of the results obtained by the proposed method were compared with those acquired by the optimised Monier-Williams method. Overall, the results from the headspace analysis showed good correlation (R = 0.9985) when compared with the conventional method. This new method requires minimal sample preparation and is simple to perform, and the analysis can also be completed within a short period of time.

Treatment planning optimisation in proton therapy

PubMed Central

McGowan, S E; Burnet, N G; Lomax, A J

2013-01-01

ABSTRACT. The goal of radiotherapy is to achieve uniform target coverage while sparing normal tissue. In proton therapy, the same sources of geometric uncertainty are present as in conventional radiotherapy. However, an important and fundamental difference in proton therapy is that protons have a finite range, highly dependent on the electron density of the material they are traversing, resulting in a steep dose gradient at the distal edge of the Bragg peak. Therefore, an accurate knowledge of the sources and magnitudes of the uncertainties affecting the proton range is essential for producing plans which are robust to these uncertainties. This review describes the current knowledge of the geometric uncertainties and discusses their impact on proton dose plans. The need for patient-specific validation is essential and in cases of complex intensity-modulated proton therapy plans the use of a planning target volume (PTV) may fail to ensure coverage of the target. In cases where a PTV cannot be used, other methods of quantifying plan quality have been investigated. A promising option is to incorporate uncertainties directly into the optimisation algorithm. A further development is the inclusion of robustness into a multicriteria optimisation framework, allowing a multi-objective Pareto optimisation function to balance robustness and conformity. The question remains as to whether adaptive therapy can become an integral part of a proton therapy, to allow re-optimisation during the course of a patient's treatment. The challenge of ensuring that plans are robust to range uncertainties in proton therapy remains, although these methods can provide practical solutions. PMID:23255545

Vibration isolation design for periodically stiffened shells by the wave finite element method

NASA Astrophysics Data System (ADS)

Hong, Jie; He, Xueqing; Zhang, Dayi; Zhang, Bing; Ma, Yanhong

2018-04-01

Periodically stiffened shell structures are widely used due to their excellent specific strength, in particular for aeronautical and astronautical components. This paper presents an improved Wave Finite Element Method (FEM) that can be employed to predict the band-gap characteristics of stiffened shell structures efficiently. An aero-engine casing, which is a typical periodically stiffened shell structure, was employed to verify the validation and efficiency of the Wave FEM. Good agreement has been found between the Wave FEM and the classical FEM for different boundary conditions. One effective wave selection method based on the Wave FEM has thus been put forward to filter the radial modes of a shell structure. Furthermore, an optimisation strategy by the combination of the Wave FEM and genetic algorithm was presented for periodically stiffened shell structures. The optimal out-of-plane band gap and the mass of the whole structure can be achieved by the optimisation strategy under an aerodynamic load. Results also indicate that geometric parameters of stiffeners can be properly selected that the out-of-plane vibration attenuates significantly in the frequency band of interest. This study can provide valuable references for designing the band gaps of vibration isolation.

Multi-Objectivising Combinatorial Optimisation Problems by Means of Elementary Landscape Decompositions.

PubMed

Ceberio, Josu; Calvo, Borja; Mendiburu, Alexander; Lozano, Jose A

2018-02-15

In the last decade, many works in combinatorial optimisation have shown that, due to the advances in multi-objective optimisation, the algorithms from this field could be used for solving single-objective problems as well. In this sense, a number of papers have proposed multi-objectivising single-objective problems in order to use multi-objective algorithms in their optimisation. In this article, we follow up this idea by presenting a methodology for multi-objectivising combinatorial optimisation problems based on elementary landscape decompositions of their objective function. Under this framework, each of the elementary landscapes obtained from the decomposition is considered as an independent objective function to optimise. In order to illustrate this general methodology, we consider four problems from different domains: the quadratic assignment problem and the linear ordering problem (permutation domain), the 0-1 unconstrained quadratic optimisation problem (binary domain), and the frequency assignment problem (integer domain). We implemented two widely known multi-objective algorithms, NSGA-II and SPEA2, and compared their performance with that of a single-objective GA. The experiments conducted on a large benchmark of instances of the four problems show that the multi-objective algorithms clearly outperform the single-objective approaches. Furthermore, a discussion on the results suggests that the multi-objective space generated by this decomposition enhances the exploration ability, thus permitting NSGA-II and SPEA2 to obtain better results in the majority of the tested instances.

Structured Syncope Care Pathways Based on Lean Six Sigma Methodology Optimises Resource Use with Shorter Time to Diagnosis and Increased Diagnostic Yield

PubMed Central

Martens, Leon; Goode, Grahame; Wold, Johan F. H.; Beck, Lionel; Martin, Georgina; Perings, Christian; Stolt, Pelle; Baggerman, Lucas

2014-01-01

Aims To conduct a pilot study on the potential to optimise care pathways in syncope/Transient Loss of Consciousness management by using Lean Six Sigma methodology while maintaining compliance with ESC and/or NICE guidelines. Methods Five hospitals in four European countries took part. The Lean Six Sigma methodology consisted of 3 phases: 1) Assessment phase, in which baseline performance was mapped in each centre, processes were evaluated and a new operational model was developed with an improvement plan that included best practices and change management; 2) Improvement phase, in which optimisation pathways and standardised best practice tools and forms were developed and implemented. Staff were trained on new processes and change-management support provided; 3) Sustaining phase, which included support, refinement of tools and metrics. The impact of the implementation of new pathways was evaluated on number of tests performed, diagnostic yield, time to diagnosis and compliance with guidelines. One hospital with focus on geriatric populations was analysed separately from the other four. Results With the new pathways, there was a 59% reduction in the average time to diagnosis (p = 0.048) and a 75% increase in diagnostic yield (p = 0.007). There was a marked reduction in repetitions of diagnostic tests and improved prioritisation of indicated tests. Conclusions Applying a structured Lean Six Sigma based methodology to pathways for syncope management has the potential to improve time to diagnosis and diagnostic yield. PMID:24927475

Hydroxyapatite, fluor-hydroxyapatite and fluorapatite produced via the sol-gel method. Optimisation, characterisation and rheology.

PubMed

Tredwin, Christopher J; Young, Anne M; Georgiou, George; Shin, Song-Hee; Kim, Hae-Won; Knowles, Jonathan C

2013-02-01

Currently, most titanium implant coatings are made using hydroxyapatite and a plasma spraying technique. There are however limitations associated with plasma spraying processes including poor adherence, high porosity and cost. An alternative method utilising the sol-gel technique offers many potential advantages but is currently lacking research data for this application. It was the objective of this study to characterise and optimise the production of Hydroxyapatite (HA), fluorhydroxyapatite (FHA) and fluorapatite (FA) using a sol-gel technique and assess the rheological properties of these materials. HA, FHA and FA were synthesised by a sol-gel method. Calcium nitrate and triethylphosphite were used as precursors under an ethanol-water based solution. Different amounts of ammonium fluoride (NH4F) were incorporated for the preparation of the sol-gel derived FHA and FA. Optimisation of the chemistry and subsequent characterisation of the sol-gel derived materials was carried out using X-ray Diffraction (XRD) and Differential Thermal Analysis (DTA). Rheology of the sol-gels was investigated using a viscometer and contact angle measurement. A protocol was established that allowed synthesis of HA, FHA and FA that were at least 99% phase pure. The more fluoride incorporated into the apatite structure; the lower the crystallisation temperature, the smaller the unit cell size (changes in the a-axis), the higher the viscosity and contact angle of the sol-gel derived apatite. A technique has been developed for the production of HA, FHA and FA by the sol-gel technique. Increasing fluoride substitution in the apatite structure alters the potential coating properties. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Intelligent inversion method for pre-stack seismic big data based on MapReduce

NASA Astrophysics Data System (ADS)

Yan, Xuesong; Zhu, Zhixin; Wu, Qinghua

2018-01-01

Seismic exploration is a method of oil exploration that uses seismic information; that is, according to the inversion of seismic information, the useful information of the reservoir parameters can be obtained to carry out exploration effectively. Pre-stack data are characterised by a large amount of data, abundant information, and so on, and according to its inversion, the abundant information of the reservoir parameters can be obtained. Owing to the large amount of pre-stack seismic data, existing single-machine environments have not been able to meet the computational needs of the huge amount of data; thus, the development of a method with a high efficiency and the speed to solve the inversion problem of pre-stack seismic data is urgently needed. The optimisation of the elastic parameters by using a genetic algorithm easily falls into a local optimum, which results in a non-obvious inversion effect, especially for the optimisation effect of the density. Therefore, an intelligent optimisation algorithm is proposed in this paper and used for the elastic parameter inversion of pre-stack seismic data. This algorithm improves the population initialisation strategy by using the Gardner formula and the genetic operation of the algorithm, and the improved algorithm obtains better inversion results when carrying out a model test with logging data. All of the elastic parameters obtained by inversion and the logging curve of theoretical model are fitted well, which effectively improves the inversion precision of the density. This algorithm was implemented with a MapReduce model to solve the seismic big data inversion problem. The experimental results show that the parallel model can effectively reduce the running time of the algorithm.

Physically-Based Assessment of Intrinsic Groundwater Resource Vulnerability in AN Urban Catchment

NASA Astrophysics Data System (ADS)

Graf, T.; Therrien, R.; Lemieux, J.; Molson, J. W.

2013-12-01

Several methods exist to assess intrinsic groundwater (re)source vulnerability for the purpose of sustainable groundwater management and protection. However, several methods are empirical and limited in their application to specific types of hydrogeological systems. Recent studies suggest that a physically-based approach could be better suited to provide a general, conceptual and operational basis for groundwater vulnerability assessment. A novel method for physically-based assessment of intrinsic aquifer vulnerability is currently under development and tested to explore the potential of an integrated modelling approach, combining groundwater travel time probability and future scenario modelling in conjunction with the fully integrated HydroGeoSphere model. To determine the intrinsic groundwater resource vulnerability, a fully coupled 2D surface water and 3D variably-saturated groundwater flow model in conjunction with a 3D geological model (GoCAD) has been developed for a case study of the Rivière Saint-Charles (Québec/Canada) regional scale, urban watershed. The model has been calibrated under transient flow conditions for the hydrogeological, variably-saturated subsurface system, coupled with the overland flow zone by taking into account monthly recharge variation and evapotranspiration. To better determine the intrinsic groundwater vulnerability, two independent approaches are considered and subsequently combined in a simple, holistic multi-criteria-decision analyse. Most data for the model comes from an extensive hydrogeological database for the watershed, whereas data gaps have been complemented via field tests and literature review. The subsurface is composed of nine hydrofacies, ranging from unconsolidated fluvioglacial sediments to low permeability bedrock. The overland flow zone is divided into five major zones (Urban, Rural, Forest, River and Lake) to simulate the differences in landuse, whereas the unsaturated zone is represented via the model integrated Van-Genuchten function. The model setup and optimisation turn out to be the most challenging part because of the non-trivial nature (due to the highly non-linear PDEs) of the coupling procedure between the surface and subsurface domain, while keeping realistic parameter ranges and obtaining realistic simulation results in both domains. The model calibration is based on water level monitoring as well as daily mean river discharge measurement at different gauge stations within the catchment. It is intended to create multiple model outcomes for the numerical modelling of the groundwater vulnerability to take into account uncertainty due to the model input data. The next step of the overall vulnerability assessment consists in modelling future vulnerability scenario(s), applying realistic changes to the model by using PEST with SENSAN for subsequent sensitivity analysis. The PEST model could also potentially be used for a model recalibration as a function of the model parameters sensitivity (simple perturbation method). Preliminary results showing a good fit between the observed and simulated water levels and hydrographs. However the simulated water depth at the overland flow domain as well as the simulated saturation distribution in the porous media domain are still showing room for improvement of the numerical model.

Efficient exploration of chemical space by fragment-based screening.

PubMed

Hall, Richard J; Mortenson, Paul N; Murray, Christopher W

2014-01-01

Screening methods seek to sample a vast chemical space in order to identify starting points for further chemical optimisation. Fragment based drug discovery exploits the superior sampling of chemical space that can be achieved when the molecular weight is restricted. Here we show that commercially available fragment space is still relatively poorly sampled and argue for highly sensitive screening methods to allow the detection of smaller fragments. We analyse the properties of our fragment library versus the properties of X-ray hits derived from the library. We particularly consider properties related to the degree of planarity of the fragments. Copyright © 2014 Elsevier Ltd. All rights reserved.

High-End Concept Based on Hypersonic Two-Stage Rocket and Electro-Magnetic Railgun to Launch Micro-Satellites Into Low-Earth

NASA Astrophysics Data System (ADS)

Bozic, O.; Longo, J. M.; Giese, P.; Behren, J.

2005-02-01

The electromagnetic railgun technology appears to be an interesting alternative to launch small payloads into Low Earth Orbit (LEO), as this may introduce lower launch costs. A high-end solution, based upon present state of the art technology, has been investigated to derive the technical boundary conditions for the application of such a new system. This paper presents the main concept and the design aspects of such propelled projectile with special emphasis on flight mechanics, aero-/thermodynamics, materials and propulsion characteristics. Launch angles and trajectory optimisation analyses are carried out by means of 3 degree of freedom simulations (3DOF). The aerodynamic form of the projectile is optimised to provoke minimum drag and low heat loads. The surface temperature distribution for critical zones is calculated with DLR developed Navier-Stokes codes TAU, HOTSOSE, whereas the engineering tool HF3T is used for time dependent calculations of heat loads and temperatures on project surface and inner structures. Furthermore, competing propulsions systems are considered for the rocket engines of both stages. The structural mass is analysed mostly on the basis of carbon fibre reinforced materials as well as classical aerospace metallic materials. Finally, this paper gives a critical overview of the technical feasibility and cost of small rockets for such missions. Key words: micro-satellite, two-stage-rocket, railgun, rocket-engines, aero/thermodynamic, mass optimization

Probabilistic parameter estimation in a 2-step chemical kinetics model for n-dodecane jet autoignition

NASA Astrophysics Data System (ADS)

Hakim, Layal; Lacaze, Guilhem; Khalil, Mohammad; Sargsyan, Khachik; Najm, Habib; Oefelein, Joseph

2018-05-01

This paper demonstrates the development of a simple chemical kinetics model designed for autoignition of n-dodecane in air using Bayesian inference with a model-error representation. The model error, i.e. intrinsic discrepancy from a high-fidelity benchmark model, is represented by allowing additional variability in selected parameters. Subsequently, we quantify predictive uncertainties in the results of autoignition simulations of homogeneous reactors at realistic diesel engine conditions. We demonstrate that these predictive error bars capture model error as well. The uncertainty propagation is performed using non-intrusive spectral projection that can also be used in principle with larger scale computations, such as large eddy simulation. While the present calibration is performed to match a skeletal mechanism, it can be done with equal success using experimental data only (e.g. shock-tube measurements). Since our method captures the error associated with structural model simplifications, we believe that the optimised model could then lead to better qualified predictions of autoignition delay time in high-fidelity large eddy simulations than the existing detailed mechanisms. This methodology provides a way to reduce the cost of reaction kinetics in simulations systematically, while quantifying the accuracy of predictions of important target quantities.

Uranium adsorption on weathered schist - Intercomparison of modeling approaches

USGS Publications Warehouse

Payne, T.E.; Davis, J.A.; Ochs, M.; Olin, M.; Tweed, C.J.

2004-01-01

Experimental data for uranium adsorption on a complex weathered rock were simulated by twelve modelling teams from eight countries using surface complexation (SC) models. This intercomparison was part of an international project to evaluate the present capabilities and limitations of SC models in representing sorption by geologic materials. The models were assessed in terms of their predictive ability, data requirements, number of optimised parameters, ability to simulate diverse chemical conditions and transferability to other substrates. A particular aim was to compare the generalised composite (GC) and component additivity (CA) approaches for modelling sorption by complex substrates. Both types of SC models showed a promising capability to simulate sorption data obtained across a range of chemical conditions. However, the models incorporated a wide variety of assumptions, particularly in terms of input parameters such as site densities and surface site types. Furthermore, the methods used to extrapolate the model simulations to different weathered rock samples collected at the same field site tended to be unsatisfactory. The outcome of this modelling exercise provides an overview of the present status of adsorption modelling in the context of radionuclide migration as practised in a number of countries worldwide.

Chromatic illumination discrimination ability reveals that human colour constancy is optimised for blue daylight illuminations.

PubMed

Pearce, Bradley; Crichton, Stuart; Mackiewicz, Michal; Finlayson, Graham D; Hurlbert, Anya

2014-01-01

The phenomenon of colour constancy in human visual perception keeps surface colours constant, despite changes in their reflected light due to changing illumination. Although colour constancy has evolved under a constrained subset of illuminations, it is unknown whether its underlying mechanisms, thought to involve multiple components from retina to cortex, are optimised for particular environmental variations. Here we demonstrate a new method for investigating colour constancy using illumination matching in real scenes which, unlike previous methods using surface matching and simulated scenes, allows testing of multiple, real illuminations. We use real scenes consisting of solid familiar or unfamiliar objects against uniform or variegated backgrounds and compare discrimination performance for typical illuminations from the daylight chromaticity locus (approximately blue-yellow) and atypical spectra from an orthogonal locus (approximately red-green, at correlated colour temperature 6700 K), all produced in real time by a 10-channel LED illuminator. We find that discrimination of illumination changes is poorer along the daylight locus than the atypical locus, and is poorest particularly for bluer illumination changes, demonstrating conversely that surface colour constancy is best for blue daylight illuminations. Illumination discrimination is also enhanced, and therefore colour constancy diminished, for uniform backgrounds, irrespective of the object type. These results are not explained by statistical properties of the scene signal changes at the retinal level. We conclude that high-level mechanisms of colour constancy are biased for the blue daylight illuminations and variegated backgrounds to which the human visual system has typically been exposed.

Design and analysis of compact MMIC switches utilising GaAs pHEMTs in 3D multilayer technology

NASA Astrophysics Data System (ADS)

Haris, Norshakila; Kyabaggu, Peter B. K.; Alim, Mohammad A.; Rezazadeh, Ali A.

2017-05-01

In this paper, we demonstrate for the first time the implementation of three-dimensional multilayer technology on GaAs-based pseudomorphic high electron mobility transistor (pHEMT) switches. Two types of pHEMT switches are considered, namely single-pole single-throw (SPST) and single-pole double-throw (SPDT). The design and analysis of the devices are demonstrated first through a simulation of the industry-recognised standard model, TriQuint’s Own Model—Level 3, developed by TriQuint Semiconductor, Inc. From the simulation analysis, three optimised SPST and SPDT pHEMT switches which can address applications ranging from L to X bands, are fabricated and tested. The performance of the pHEMT switches using multilayer technology are comparable to those of the current state-of-the-art pHEMT switches, while simultaneously offering compact circuits with the advantages of integration with other MMIC components.

Wiener-Hammerstein system identification - an evolutionary approach

NASA Astrophysics Data System (ADS)

Naitali, Abdessamad; Giri, Fouad

2016-01-01

The problem of identifying parametric Wiener-Hammerstein (WH) systems is addressed within the evolutionary optimisation context. Specifically, a hybrid culture identification method is developed that involves model structure adaptation using genetic recombination and model parameter learning using particle swarm optimisation. The method enjoys three interesting features: (1) the risk of premature convergence of model parameter estimates to local optima is significantly reduced, due to the constantly maintained diversity of model candidates; (2) no prior knowledge is needed except for upper bounds on the system structure indices; (3) the method is fully autonomous as no interaction is needed with the user during the optimum search process. The performances of the proposed method will be illustrated and compared to alternative methods using a well-established WH benchmark.

Shape and energy consistent pseudopotentials for correlated electron systems

PubMed Central

Needs, R. J.

2017-01-01

A method is developed for generating pseudopotentials for use in correlated-electron calculations. The paradigms of shape and energy consistency are combined and defined in terms of correlated-electron wave-functions. The resulting energy consistent correlated electron pseudopotentials (eCEPPs) are constructed for H, Li–F, Sc–Fe, and Cu. Their accuracy is quantified by comparing the relaxed molecular geometries and dissociation energies which they provide with all electron results, with all quantities evaluated using coupled cluster singles, doubles, and triples calculations. Errors inherent in the pseudopotentials are also compared with those arising from a number of approximations commonly used with pseudopotentials. The eCEPPs provide a significant improvement in optimised geometries and dissociation energies for small molecules, with errors for the latter being an order-of-magnitude smaller than for Hartree-Fock-based pseudopotentials available in the literature. Gaussian basis sets are optimised for use with these pseudopotentials. PMID:28571391

Strong constraint on modelled global carbon uptake using solar-induced chlorophyll fluorescence data.

PubMed

MacBean, Natasha; Maignan, Fabienne; Bacour, Cédric; Lewis, Philip; Peylin, Philippe; Guanter, Luis; Köhler, Philipp; Gómez-Dans, Jose; Disney, Mathias

2018-01-31

Accurate terrestrial biosphere model (TBM) simulations of gross carbon uptake (gross primary productivity - GPP) are essential for reliable future terrestrial carbon sink projections. However, uncertainties in TBM GPP estimates remain. Newly-available satellite-derived sun-induced chlorophyll fluorescence (SIF) data offer a promising direction for addressing this issue by constraining regional-to-global scale modelled GPP. Here, we use monthly 0.5° GOME-2 SIF data from 2007 to 2011 to optimise GPP parameters of the ORCHIDEE TBM. The optimisation reduces GPP magnitude across all vegetation types except C4 plants. Global mean annual GPP therefore decreases from 194 ± 57 PgCyr -1 to 166 ± 10 PgCyr -1 , bringing the model more in line with an up-scaled flux tower estimate of 133 PgCyr -1 . Strongest reductions in GPP are seen in boreal forests: the result is a shift in global GPP distribution, with a ~50% increase in the tropical to boreal productivity ratio. The optimisation resulted in a greater reduction in GPP than similar ORCHIDEE parameter optimisation studies using satellite-derived NDVI from MODIS and eddy covariance measurements of net CO 2 fluxes from the FLUXNET network. Our study shows that SIF data will be instrumental in constraining TBM GPP estimates, with a consequent improvement in global carbon cycle projections.

Development and Optimisation of an HPLC-DAD-ESI-Q-ToF Method for the Determination of Phenolic Acids and Derivatives

PubMed Central

Restivo, Annalaura; Degano, Ilaria; Ribechini, Erika; Colombini, Maria Perla

2014-01-01

A method for the HPLC-MS/MS analysis of phenols, including phenolic acids and naphtoquinones, using an amide-embedded phase column was developed and compared to the literature methods based on classical C18 stationary phase columns. RP-Amide is a recently developed polar embedded stationary phase, whose wetting properties mean that up to 100% water can be used as an eluent. The increased retention and selectivity for polar compounds and the possibility of working in 100% water conditions make this column particularly interesting for the HPLC analysis of phenolic acids and derivatives. In this study, the chromatographic separation was optimised on an HPLC-DAD, and was used to separate 13 standard phenolic acids and derivatives. The method was validated on an HPLC-ESI-Q-ToF. The acquisition was performed in negative polarity and MS/MS target mode. Ionisation conditions and acquisition parameters for the Q-ToF detector were investigated by working on collision energies and fragmentor potentials. The performance of the method was fully evaluated on standards. Moreover, several raw materials containing phenols were analysed: walnut, gall, wine, malbec grape, French oak, red henna and propolis. Our method allowed us to characterize the phenolic composition in a wide range of matrices and to highlight possible matrix effects. PMID:24551158

Scientific discovery as a combinatorial optimisation problem: How best to navigate the landscape of possible experiments?

PubMed Central

Kell, Douglas B

2012-01-01

A considerable number of areas of bioscience, including gene and drug discovery, metabolic engineering for the biotechnological improvement of organisms, and the processes of natural and directed evolution, are best viewed in terms of a ‘landscape’ representing a large search space of possible solutions or experiments populated by a considerably smaller number of actual solutions that then emerge. This is what makes these problems ‘hard’, but as such these are to be seen as combinatorial optimisation problems that are best attacked by heuristic methods known from that field. Such landscapes, which may also represent or include multiple objectives, are effectively modelled in silico, with modern active learning algorithms such as those based on Darwinian evolution providing guidance, using existing knowledge, as to what is the ‘best’ experiment to do next. An awareness, and the application, of these methods can thereby enhance the scientific discovery process considerably. This analysis fits comfortably with an emerging epistemology that sees scientific reasoning, the search for solutions, and scientific discovery as Bayesian processes. PMID:22252984

Scientific discovery as a combinatorial optimisation problem: how best to navigate the landscape of possible experiments?

PubMed

Kell, Douglas B

2012-03-01

A considerable number of areas of bioscience, including gene and drug discovery, metabolic engineering for the biotechnological improvement of organisms, and the processes of natural and directed evolution, are best viewed in terms of a 'landscape' representing a large search space of possible solutions or experiments populated by a considerably smaller number of actual solutions that then emerge. This is what makes these problems 'hard', but as such these are to be seen as combinatorial optimisation problems that are best attacked by heuristic methods known from that field. Such landscapes, which may also represent or include multiple objectives, are effectively modelled in silico, with modern active learning algorithms such as those based on Darwinian evolution providing guidance, using existing knowledge, as to what is the 'best' experiment to do next. An awareness, and the application, of these methods can thereby enhance the scientific discovery process considerably. This analysis fits comfortably with an emerging epistemology that sees scientific reasoning, the search for solutions, and scientific discovery as Bayesian processes. Copyright © 2012 WILEY Periodicals, Inc.

Integrating professionalism teaching into undergraduate medical education in the UK setting.

PubMed

Goldie, John

2008-06-01

This paper examines how professionalism teaching might be integrated into undergraduate medical education in the United Kingdom setting. It advocates adopting an outcome-based approach to curriculum planning, using the Scottish Deans' Medical Curriculum Group's (SDMCG) outcomes as a starting point. In discussing the curricular content, potential learning methods and strategies, theoretical considerations are explored. Student selection, assessment and strategies for optimising the educational environment are also considered.

Pure random search for ambient sensor distribution optimisation in a smart home environment.

PubMed

Poland, Michael P; Nugent, Chris D; Wang, Hui; Chen, Liming

2011-01-01

Smart homes are living spaces facilitated with technology to allow individuals to remain in their own homes for longer, rather than be institutionalised. Sensors are the fundamental physical layer with any smart home, as the data they generate is used to inform decision support systems, facilitating appropriate actuator actions. Positioning of sensors is therefore a fundamental characteristic of a smart home. Contemporary smart home sensor distribution is aligned to either a) a total coverage approach; b) a human assessment approach. These methods for sensor arrangement are not data driven strategies, are unempirical and frequently irrational. This Study hypothesised that sensor deployment directed by an optimisation method that utilises inhabitants' spatial frequency data as the search space, would produce more optimal sensor distributions vs. the current method of sensor deployment by engineers. Seven human engineers were tasked to create sensor distributions based on perceived utility for 9 deployment scenarios. A Pure Random Search (PRS) algorithm was then tasked to create matched sensor distributions. The PRS method produced superior distributions in 98.4% of test cases (n=64) against human engineer instructed deployments when the engineers had no access to the spatial frequency data, and in 92.0% of test cases (n=64) when engineers had full access to these data. These results thus confirmed the hypothesis.

Filter-Based Dispersion-Managed Versatile Ultrafast Fibre Laser

PubMed Central

Peng, Junsong; Boscolo, Sonia

2016-01-01

We present the operation of an ultrafast passively mode-locked fibre laser, in which flexible control of the pulse formation mechanism is readily realised by an in-cavity programmable filter the dispersion and bandwidth of which can be software configured. We show that conventional soliton, dispersion-managed (DM) soliton (stretched-pulse) and dissipative soliton mode-locking regimes can be reliably targeted by changing the filter’s dispersion and bandwidth only, while no changes are made to the physical layout of the laser cavity. Numerical simulations are presented which confirm the different nonlinear pulse evolutions inside the laser cavity. The proposed technique holds great potential for achieving a high degree of control over the dynamics and output of ultrafast fibre lasers, in contrast to the traditional method to control the pulse formation mechanism in a DM fibre laser, which involves manual optimisation of the relative length of fibres with opposite-sign dispersion in the cavity. Our versatile ultrafast fibre laser will be attractive for applications requiring different pulse profiles such as in optical signal processing and optical communications. PMID:27183882

Optimised detection of mitochondrial DNA strand breaks.

PubMed

Hanna, Rebecca; Crowther, Jonathan M; Bulsara, Pallav A; Wang, Xuying; Moore, David J; Birch-Machin, Mark A

2018-05-04

Intrinsic and extrinsic factors that induce cellular oxidative stress damage tissue integrity and promote ageing, resulting in accumulative strand breaks to the mitochondrial DNA (mtDNA) genome. Limited repair mechanisms and close proximity to superoxide generation make mtDNA a prominent biomarker of oxidative damage. Using human DNA we describe an optimised long-range qPCR methodology that sensitively detects mtDNA strand breaks relative to a suite of short mitochondrial and nuclear DNA housekeeping amplicons, which control for any variation in mtDNA copy number. An application is demonstrated by detecting 16-36-fold mtDNA damage in human skin cells induced by hydrogen peroxide and solar simulated radiation. Copyright © 2018 Elsevier B.V. and Mitochondria Research Society. All rights reserved.

Sustainable Mining Land Use for Lignite Based Energy Projects

NASA Astrophysics Data System (ADS)

Dudek, Michal; Krysa, Zbigniew

2017-12-01

This research aims to discuss complex lignite based energy projects economic viability and its impact on sustainable land use with respect to project risk and uncertainty, economics, optimisation (e.g. Lerchs and Grossmann) and importance of lignite as fuel that may be expressed in situ as deposit of energy. Sensitivity analysis and simulation consist of estimated variable land acquisition costs, geostatistics, 3D deposit block modelling, electricity price considered as project product price, power station efficiency and power station lignite processing unit cost, CO2 allowance costs, mining unit cost and also lignite availability treated as lignite reserves kriging estimation error. Investigated parameters have nonlinear influence on results so that economically viable amount of lignite in optimal pit varies having also nonlinear impact on land area required for mining operation.

Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations

NASA Astrophysics Data System (ADS)

Misini Ignjatović, Majda; Caldararu, Octav; Dong, Geng; Muñoz-Gutierrez, Camila; Adasme-Carreño, Francisco; Ryde, Ulf

2016-09-01

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970-1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.

Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations.

PubMed

Misini Ignjatović, Majda; Caldararu, Octav; Dong, Geng; Muñoz-Gutierrez, Camila; Adasme-Carreño, Francisco; Ryde, Ulf

2016-09-01

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970-1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.

Relative Displacement Method for Track-Structure Interaction

PubMed Central

Ramos, Óscar Ramón; Pantaleón, Marcos J.

2014-01-01

The track-structure interaction effects are usually analysed with conventional FEM programs, where it is difficult to implement the complex track-structure connection behaviour, which is nonlinear, elastic-plastic and depends on the vertical load. The authors developed an alternative analysis method, which they call the relative displacement method. It is based on the calculation of deformation states in single DOF element models that satisfy the boundary conditions. For its solution, an iterative optimisation algorithm is used. This method can be implemented in any programming language or analysis software. A comparison with ABAQUS calculations shows a very good result correlation and compliance with the standard's specifications. PMID:24634610

Allocation of solid waste collection bins and route optimisation using geographical information system: A case study of Dhanbad City, India.

PubMed

Khan, D; Samadder, S R

2016-07-01

Collection of municipal solid waste is one of the most important elements of municipal waste management and requires maximum fund allocated for waste management. The cost of collection and transportation can be reduced in comparison with the present scenario if the solid waste collection bins are located at suitable places so that the collection routes become minimum. This study presents a suitable solid waste collection bin allocation method at appropriate places with uniform distance and easily accessible location so that the collection vehicle routes become minimum for the city Dhanbad, India. The network analyst tool set available in ArcGIS was used to find the optimised route for solid waste collection considering all the required parameters for solid waste collection efficiently. These parameters include the positions of solid waste collection bins, the road network, the population density, waste collection schedules, truck capacities and their characteristics. The present study also demonstrates the significant cost reductions that can be obtained compared with the current practices in the study area. The vehicle routing problem solver tool of ArcGIS was used to identify the cost-effective scenario for waste collection, to estimate its running costs and to simulate its application considering both travel time and travel distance simultaneously. © The Author(s) 2016.

Optimisation techniques in vaginal cuff brachytherapy.

PubMed

Tuncel, N; Garipagaoglu, M; Kizildag, A U; Andic, F; Toy, A

2009-11-01

The aim of this study was to explore whether an in-house dosimetry protocol and optimisation method are able to produce a homogeneous dose distribution in the target volume, and how often optimisation is required in vaginal cuff brachytherapy. Treatment planning was carried out for 109 fractions in 33 patients who underwent high dose rate iridium-192 (Ir(192)) brachytherapy using Fletcher ovoids. Dose prescription and normalisation were performed to catheter-oriented lateral dose points (dps) within a range of 90-110% of the prescribed dose. The in-house vaginal apex point (Vk), alternative vaginal apex point (Vk'), International Commission on Radiation Units and Measurements (ICRU) rectal point (Rg) and bladder point (Bl) doses were calculated. Time-position optimisations were made considering dps, Vk and Rg doses. Keeping the Vk dose higher than 95% and the Rg dose less than 85% of the prescribed dose was intended. Target dose homogeneity, optimisation frequency and the relationship between prescribed dose, Vk, Vk', Rg and ovoid diameter were investigated. The mean target dose was 99+/-7.4% of the prescription dose. Optimisation was required in 92 out of 109 (83%) fractions. Ovoid diameter had a significant effect on Rg (p = 0.002), Vk (p = 0.018), Vk' (p = 0.034), minimum dps (p = 0.021) and maximum dps (p<0.001). Rg, Vk and Vk' doses with 2.5 cm diameter ovoids were significantly higher than with 2 cm and 1.5 cm ovoids. Catheter-oriented dose point normalisation provided a homogeneous dose distribution with a 99+/-7.4% mean dose within the target volume, requiring time-position optimisation.

Performance assessment and optimisation of a large information system by combined customer relationship management and resilience engineering: a mathematical programming approach

NASA Astrophysics Data System (ADS)

Azadeh, A.; Foroozan, H.; Ashjari, B.; Motevali Haghighi, S.; Yazdanparast, R.; Saberi, M.; Torki Nejad, M.

2017-10-01

ISs and ITs play a critical role in large complex gas corporations. Many factors such as human, organisational and environmental factors affect IS in an organisation. Therefore, investigating ISs success is considered to be a complex problem. Also, because of the competitive business environment and the high amount of information flow in organisations, new issues like resilient ISs and successful customer relationship management (CRM) have emerged. A resilient IS will provide sustainable delivery of information to internal and external customers. This paper presents an integrated approach to enhance and optimise the performance of each component of a large IS based on CRM and resilience engineering (RE) in a gas company. The enhancement of the performance can help ISs to perform business tasks efficiently. The data are collected from standard questionnaires. It is then analysed by data envelopment analysis by selecting the optimal mathematical programming approach. The selected model is validated and verified by principle component analysis method. Finally, CRM and RE factors are identified as influential factors through sensitivity analysis for this particular case study. To the best of our knowledge, this is the first study for performance assessment and optimisation of large IS by combined RE and CRM.

A new paradigm in personal dosimetry using LiF:Mg,Cu,P.

PubMed

Cassata, J R; Moscovitch, M; Rotunda, J E; Velbeck, K J

2002-01-01

The United States Navy has been monitoring personnel for occupational exposure to ionising radiation since 1947. Film was exclusively used until 1973 when thermoluminescence dosemeters were introduced and used to the present time. In 1994, a joint research project between the Naval Dosimetry Center, Georgetown University, and Saint Gobain Crystals and Detectors (formerly Bicron RMP formerly Harshaw TLD) began to develop a state of the art thermoluminescent dosimetry system. The study was conducted from a large-scale dosimetry processor point of view with emphasis on a systems approach. Significant improvements were achieved by replacing the LiF:Mg,Ti with LiF:Mg,Cu,P TL elements due to the significant sensitivity increase, linearity, and negligible hiding. Dosemeter filters were optimised for gamma and X ray energy discrimination using Monte Carlo modelling (MCNP) resulting in significant improvement in accuracy and precision. Further improvements were achieved through the use of neural-network based dose calculation algorithms. Both back propagation and functional link methods were implemented and the data compared with essentially the same results. Several operational aspects of the system are discussed, including (1) background subtraction using control dosemeters, (2) selection criteria for control dosemeters, (3) optimisation of the TLD readers, (4) calibration methodology, and (5) the optimisation of the heating profile.

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

PubMed

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.

Incorporation of MRI-AIF Information For Improved Kinetic Modelling of Dynamic PET Data

NASA Astrophysics Data System (ADS)

Sari, Hasan; Erlandsson, Kjell; Thielemans, Kris; Atkinson, David; Ourselin, Sebastien; Arridge, Simon; Hutton, Brian F.

2015-06-01

In the analysis of dynamic PET data, compartmental kinetic analysis methods require an accurate knowledge of the arterial input function (AIF). Although arterial blood sampling is the gold standard of the methods used to measure the AIF, it is usually not preferred as it is an invasive method. An alternative method is the simultaneous estimation method (SIME), where physiological parameters and the AIF are estimated together, using information from different anatomical regions. Due to the large number of parameters to estimate in its optimisation, SIME is a computationally complex method and may sometimes fail to give accurate estimates. In this work, we try to improve SIME by utilising an input function derived from a simultaneously obtained DSC-MRI scan. With the assumption that the true value of one of the six parameter PET-AIF model can be derived from an MRI-AIF, the method is tested using simulated data. The results indicate that SIME can yield more robust results when the MRI information is included with a significant reduction in absolute bias of Ki estimates.

Energy landscapes for a machine learning application to series data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ballard, Andrew J.; Stevenson, Jacob D.; Das, Ritankar

2016-03-28

Methods developed to explore and characterise potential energy landscapes are applied to the corresponding landscapes obtained from optimisation of a cost function in machine learning. We consider neural network predictions for the outcome of local geometry optimisation in a triatomic cluster, where four distinct local minima exist. The accuracy of the predictions is compared for fits using data from single and multiple points in the series of atomic configurations resulting from local geometry optimisation and for alternative neural networks. The machine learning solution landscapes are visualised using disconnectivity graphs, and signatures in the effective heat capacity are analysed in termsmore » of distributions of local minima and their properties.« less

Optimisation by hierarchical search

NASA Astrophysics Data System (ADS)

Zintchenko, Ilia; Hastings, Matthew; Troyer, Matthias

2015-03-01

Finding optimal values for a set of variables relative to a cost function gives rise to some of the hardest problems in physics, computer science and applied mathematics. Although often very simple in their formulation, these problems have a complex cost function landscape which prevents currently known algorithms from efficiently finding the global optimum. Countless techniques have been proposed to partially circumvent this problem, but an efficient method is yet to be found. We present a heuristic, general purpose approach to potentially improve the performance of conventional algorithms or special purpose hardware devices by optimising groups of variables in a hierarchical way. We apply this approach to problems in combinatorial optimisation, machine learning and other fields.

Computer simulation of electron flow in linear-beam microwave tubes

NASA Astrophysics Data System (ADS)

Kumar, Lalit

1990-12-01

The computer simulation of electron flow in linear-beam microwave tubes, such as a travelling-wave tube (TWT) and klystron, is used for designing and optimising the electron gun and collector and for analysing the large-signal beam-wave interaction phenomenon. Major aspects of simulation of electron flow in static and rf fields present in such tubes are discussed. Some advancements made in this respect and results obtained from computer programs developed by the research group at CEERI for a gridded electron gun, depressed collector, and large-signal analysis of TWT and klystron are presented.

A cost-effective method for simulating city-wide air flow and pollutant dispersion at building resolving scale

NASA Astrophysics Data System (ADS)

Berchet, Antoine; Zink, Katrin; Muller, Clive; Oettl, Dietmar; Brunner, Juerg; Emmenegger, Lukas; Brunner, Dominik

2017-06-01

A cost-effective method is presented allowing to simulate the air flow and pollutant dispersion in a whole city over multiple years at the building-resolving scale with hourly time resolution. This combination of high resolution and long time span is critically needed for epidemiological studies and for air pollution control, but still poses a great challenge for current state-of-the-art modelling techniques. The presented method relies on the pre-computation of a discrete set of possible weather situations and corresponding steady-state flow and dispersion patterns. The most suitable situation for any given hour is then selected by matching the simulated wind patterns to meteorological observations in and around the city. The catalogue of pre-computed situations corresponds to different large-scale forcings in terms of wind speed, wind direction and stability. A meteorological model converts these forcings into realistic mesoscale flow patterns accounting for the effects of topography and land-use contrasts in a domain covering the city and its surroundings. These mesoscale patterns serve as boundary conditions for a microscale urban flow model which finally drives a Lagrangian air pollutant dispersion model. The method is demonstrated with the modelling system GRAMM/GRAL v14.8 for two Swiss cities in complex terrain, Zurich and Lausanne. The mesoscale flow patterns in the two regions of interest, dominated by land-lake breezes and driven by the partly steep topography, are well reproduced in the simulations matched to in situ observations. In particular, the combination of wind measurements at different locations around the city appeared to be a robust approach to deduce the stability class for the boundary layer within the city. This information is critical for predicting the temporal variability of pollution concentration within the city, regarding their relationship with the intensity of horizontal and vertical dispersion and of turbulence. In the vicinity of sources, the 5 m resolution chosen in our set-up is not always sufficient to reproduce the very steep concentration gradients, pointing at additional cost optimisations in the method required to make higher resolutions affordable. Nevertheless, the catalogue-based methodology allows reproducing concentration variability very consistently further away from emission sources, hence for most parts of the city.

Influence of short rear end tapers on the wake of a simplified square-back vehicle: wake topology and rear drag

NASA Astrophysics Data System (ADS)

Perry, Anna-Kristina; Pavia, Giancarlo; Passmore, Martin

2016-11-01

As vehicle manufacturers work to reduce energy consumption of all types of vehicles, external vehicle aerodynamics has become increasingly important. Whilst production vehicle shape optimisation methods are well developed, the need to make further advances requires deeper understanding of the highly three-dimensional flow around bluff bodies. In this paper, the wake flow of a generic bluff body, the Windsor body, based on a square-back car geometry, was investigated by means of balance measurements, surface pressure measurements and 2D particle image velocimetry planes. Changes in the wake topology are triggered by the application of short tapers (4 % of the model length) to the top and bottom edges of the base, representing a shape optimisation that is realistic for many modern production vehicles. The base drag is calculated and correlated with the aerodynamic drag data. The results not only show the effectiveness of such small devices in modifying the time average topology of the wake but also shed some light on the effects produced by different levels of upwash and downwash on the bi-stable nature of the wake itself.

A View on Future Building System Modeling and Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wetter, Michael

This chapter presents what a future environment for building system modeling and simulation may look like. As buildings continue to require increased performance and better comfort, their energy and control systems are becoming more integrated and complex. We therefore focus in this chapter on the modeling, simulation and analysis of building energy and control systems. Such systems can be classified as heterogeneous systems because they involve multiple domains, such as thermodynamics, fluid dynamics, heat and mass transfer, electrical systems, control systems and communication systems. Also, they typically involve multiple temporal and spatial scales, and their evolution can be described bymore » coupled differential equations, discrete equations and events. Modeling and simulating such systems requires a higher level of abstraction and modularisation to manage the increased complexity compared to what is used in today's building simulation programs. Therefore, the trend towards more integrated building systems is likely to be a driving force for changing the status quo of today's building simulation programs. Thischapter discusses evolving modeling requirements and outlines a path toward a future environment for modeling and simulation of heterogeneous building systems.A range of topics that would require many additional pages of discussion has been omitted. Examples include computational fluid dynamics for air and particle flow in and around buildings, people movement, daylight simulation, uncertainty propagation and optimisation methods for building design and controls. For different discussions and perspectives on the future of building modeling and simulation, we refer to Sahlin (2000), Augenbroe (2001) and Malkawi and Augenbroe (2004).« less

A novel wavelet neural network based pathological stage detection technique for an oral precancerous condition

PubMed Central

Paul, R R; Mukherjee, A; Dutta, P K; Banerjee, S; Pal, M; Chatterjee, J; Chaudhuri, K; Mukkerjee, K

2005-01-01

Aim: To describe a novel neural network based oral precancer (oral submucous fibrosis; OSF) stage detection method. Method: The wavelet coefficients of transmission electron microscopy images of collagen fibres from normal oral submucosa and OSF tissues were used to choose the feature vector which, in turn, was used to train the artificial neural network. Results: The trained network was able to classify normal and oral precancer stages (less advanced and advanced) after obtaining the image as an input. Conclusions: The results obtained from this proposed technique were promising and suggest that with further optimisation this method could be used to detect and stage OSF, and could be adapted for other conditions. PMID:16126873

A new method for the determination of short-chain fatty acids from the aliphatic series in wines by headspace solid-phase microextraction-gas chromatography-ion trap mass spectrometry.

PubMed

Olivero, Sergio J Pérez; Trujillo, Juan P Pérez

2011-06-24

A new analytical method for the determination of nine short-chain fatty acids (acetic, propionic, isobutyric, butyric, isovaleric, 2-methylbutyric, hexanoic, octanoic and decanoic acids) in wines using the automated HS/SPME-GC-ITMS technique was developed and optimised. Five different SPME fibers were tested and the influence of different factors such as temperature and time of extraction, temperature and time of desorption, pH, strength ionic, tannins, anthocyans, SO(2), sugar and ethanol content were studied and optimised using model solutions. Some analytes showed matrix effect so a study of recoveries was performed. The proposed HS/SPME-GC-ITMS method, that covers the concentration range of the different analytes in wines, showed wide linear ranges, values of repeatability and reproducibility lower than 4.0% of RSD and detection limits between 3 and 257 μgL(-1), lower than the olfactory thresholds. The optimised method is a suitable technique for the quantitative analysis of short-chain fatty acids from the aliphatic series in real samples of white, rose and red wines. Copyright © 2011 Elsevier B.V. All rights reserved.

Optimisation and validation of the microwave-assisted extraction of phenolic compounds from rice grains.

PubMed

Setyaningsih, W; Saputro, I E; Palma, M; Barroso, C G

2015-02-15

A new microwave-assisted extraction (MAE) method has been investigated for the extraction of phenolic compounds from rice grains. The experimental conditions studied included temperature (125-175°C), microwave power (500-1000W), time (5-15min), solvent (10-90% EtOAc in MeOH) and solvent-to-sample ratio (10:1 to 20:1). The extraction variables were optimised by the response surface methodology. Extraction temperature and solvent were found to have a highly significant effect on the response value (p<0.0005) and the extraction time also had a significant effect (p<0.05). The optimised MAE conditions were as follows: extraction temperature 185°C, microwave power 1000W, extraction time 20min, solvent 100% MeOH, and solvent-to-sample ratio 10:1. The developed method had a high precision (in terms of CV: 5.3% for repeatability and 5.5% for intermediate precision). Finally, the new method was applied to real samples in order to investigate the presence of phenolic compounds in a wide variety of rice grains. Copyright © 2014 Elsevier Ltd. All rights reserved.