8 resultados para Transformation-based semi-parametric estimators
Resumo:
Adjoint methods have proven to be an efficient way of calculating the gradient of an objective function with respect to a shape parameter for optimisation, with a computational cost nearly independent of the number of the design variables [1]. The approach in this paper links the adjoint surface sensitivities (gradient of objective function with respect to the surface movement) with the parametric design velocities (movement of the surface due to a CAD parameter perturbation) in order to compute the gradient of the objective function with respect to CAD variables.
For a successful implementation of shape optimization strategies in practical industrial cases, the choice of design variables or parameterisation scheme used for the model to be optimized plays a vital role. Where the goal is to base the optimization on a CAD model the choices are to use a NURBS geometry generated from CAD modelling software, where the position of the NURBS control points are the optimisation variables [2] or to use the feature based CAD model with all of the construction history to preserve the design intent [3]. The main advantage of using the feature based model is that the optimized model produced can be directly used for the downstream applications including manufacturing and process planning.
This paper presents an approach for optimization based on the feature based CAD model, which uses CAD parameters defining the features in the model geometry as the design variables. In order to capture the CAD surface movement with respect to the change in design variable, the “Parametric Design Velocity” is calculated, which is defined as the movement of the CAD model boundary in the normal direction due to a change in the parameter value.
The approach presented here for calculating the design velocities represents an advancement in terms of capability and robustness of that described by Robinson et al. [3]. The process can be easily integrated to most industrial optimisation workflows and is immune to the topology and labelling issues highlighted by other CAD based optimisation processes. It considers every continuous (“real value”) parameter type as an optimisation variable, and it can be adapted to work with any CAD modelling software, as long as it has an API which provides access to the values of the parameters which control the model shape and allows the model geometry to be exported. To calculate the movement of the boundary the methodology employs finite differences on the shape of the 3D CAD models before and after the parameter perturbation. The implementation procedure includes calculating the geometrical movement along a normal direction between two discrete representations of the original and perturbed geometry respectively. Parametric design velocities can then be directly linked with adjoint surface sensitivities to extract the gradients to use in a gradient-based optimization algorithm.
The optimisation of a flow optimisation problem is presented, in which the power dissipation of the flow in an automotive air duct is to be reduced by changing the parameters of the CAD geometry created in CATIA V5. The flow sensitivities are computed with the continuous adjoint method for a laminar and turbulent flow [4] and are combined with the parametric design velocities to compute the cost function gradients. A line-search algorithm is then used to update the design variables and proceed further with optimisation process.
Resumo:
We consider the problem of resource selection in clustered Peer-to-Peer Information Retrieval (P2P IR) networks with cooperative peers. The clustered P2P IR framework presents a significant departure from general P2P IR architectures by employing clustering to ensure content coherence between resources at the resource selection layer, without disturbing document allocation. We propose that such a property could be leveraged in resource selection by adapting well-studied and popular inverted lists for centralized document retrieval. Accordingly, we propose the Inverted PeerCluster Index (IPI), an approach that adapts the inverted lists, in a straightforward manner, for resource selection in clustered P2P IR. IPI also encompasses a strikingly simple peer-specific scoring mechanism that exploits the said index for resource selection. Through an extensive empirical analysis on P2P IR testbeds, we establish that IPI competes well with the sophisticated state-of-the-art methods in virtually every parameter of interest for the resource selection task, in the context of clustered P2P IR.
Resumo:
The goal of this work is to present an efficient CAD-based adjoint process chain for calculating parametric sensitivities (derivatives of the objective function with respect to the CAD parameters) in timescales acceptable for industrial design processes. The idea is based on linking parametric design velocities (geometric sensitivities computed from the CAD model) with adjoint surface sensitivities. A CAD-based design velocity computation method has been implemented based on distances between discrete representations of perturbed geometries. This approach differs from other methods due to the fact that it works with existing commercial CAD packages (unlike most analytical approaches) and it can cope with the changes in CAD model topology and face labeling. Use of the proposed method allows computation of parametric sensitivities using adjoint data at a computational cost which scales with the number of objective functions being considered, while it is essentially independent of the number of design variables. The gradient computation is demonstrated on test cases for a Nozzle Guide Vane (NGV) model and a Turbine Rotor Blade model. The results are validated against finite difference values and good agreement is shown. This gradient information can be passed to an optimization algorithm, which will use it to update the CAD model parameters.
Resumo:
This paper describes an implementation of a method capable of integrating parametric, feature based, CAD models based on commercial software (CATIA) with the SU2 software framework. To exploit the adjoint based methods for aerodynamic optimisation within the SU2, a formulation to obtain geometric sensitivities directly from the commercial CAD parameterisation is introduced, enabling the calculation of gradients with respect to CAD based design variables. To assess the accuracy and efficiency of the alternative approach, two aerodynamic optimisation problems are investigated: an inviscid, 3D, problem with multiple constraints, and a 2D high-lift aerofoil, viscous problem without any constraints. Initial results show the new parameterisation obtaining reliable optimums, with similar levels of performance of the software native parameterisations. In the final paper, details of computing CAD sensitivities will be provided, including accuracy as well as linking geometric sensitivities to aerodynamic objective functions and constraints; the impact in the robustness of the overall method will be assessed and alternative parameterisations will be included.
Resumo:
We present a new approach to understand the landscape of supernova explosion energies, ejected nickel masses, and neutron star birth masses. In contrast to other recent parametric approaches, our model predicts the properties of neutrino-driven explosions based on the pre-collapse stellar structure without the need for hydrodynamic simulations. The model is based on physically motivated scaling laws and simple differential equations describing the shock propagation, the contraction of the neutron star, the neutrino emission, the heating conditions, and the explosion energetics. Using model parameters compatible with multi-D simulations and a fine grid of thousands of supernova progenitors, we obtain a variegated landscape of neutron star and black hole formation similar to other parametrized approaches and find good agreement with semi-empirical measures for the ‘explodability’ of massive stars. Our predicted explosion properties largely conform to observed correlations between the nickel mass and explosion energy. Accounting for the coexistence of outflows and downflows during the explosion phase, we naturally obtain a positive correlation between explosion energy and ejecta mass. These correlations are relatively robust against parameter variations, but our results suggest that there is considerable leeway in parametric models to widen or narrow the mass ranges for black hole and neutron star formation and to scale explosion energies up or down. Our model is currently limited to an all-or-nothing treatment of fallback and there remain some minor discrepancies between model predictions and observational constraints.
Resumo:
Background: The move toward evidence-based education has led to increasing numbers of randomised trials in schools. However, the literature on recruitment to non-clinical trials is relatively underdeveloped, when compared to that of clinical trials. Recruitment to school-based randomised trials is, however, challenging; even more so when the focus of the study is a sensitive issue such as sexual health. This article reflects on the challenges of recruiting post-primary schools, adolescent pupils and parents to a cluster randomised feasibility trial of a sexual health intervention, and the strategies employed to address them.
Methods: The Jack Trial was funded by the UK National Institute for Health Research (NIHR). It comprised a feasibility study of an interactive film-based sexual health intervention entitled If I Were Jack, recruiting over 800 adolescents from eight socio-demographically diverse post-primary schools in Northern Ireland. It aimed to determine the facilitators and barriers to recruitment and retention to a school-based sexual health trial and identify optimal multi-level strategies for an effectiveness study. As part of an embedded process evaluation, we conducted semi-structured interviews and focus groups with principals, vice-principals, teachers, pupils and parents recruited to the study as well as classroom observations and a parents’ survey.
Results: With reference to Social Learning Theory, we identified a number of individual, behavioural and environmental level factors which influenced recruitment. Commonly identified facilitators included perceptions of the relevance and potential benefit of the intervention to adolescents, the credibility of the organisation and individuals running the study, support offered by trial staff, and financial incentives. Key barriers were prior commitment to other research, lack of time and resources, and perceptions that the intervention was incompatible with pupil or parent needs or the school ethos.
Conclusions: Reflecting on the methodological challenges of recruiting to a school-based sexual health feasibility trial, this study highlights pertinent general and trial-specific facilitators and barriers to recruitment, which will prove useful for future trials with schools, adolescent pupils and parents.
Resumo:
Abstract - This study investigates the effect of solid dispersions prepared from of polyethylene glycol (PEG) 3350 and 6000 Da alone or combined with the non-ionic surfactant Tween 80 on the solubility and dissolution rate of a poorly soluble drug eprosartan mesylate (ESM) in attempt to improve its bioavailability following its oral administration.
INTRODUCTION
ESM is a potent anti-hypertension [1]. It has low water solubility and is classified as a Class II drug as per the Biopharmaceutical Classification Systems (BCS) leading to low and variable oral bioavailability (approximately 13%). [2]. Thus, improving ESM solubility and/or dissolution rate would eventually improve the drug bioavailability. Solid dispersion is widely used technique to improve the water solubility of poorly water-soluble drugs employing various biocompatible polymers. In this study, we aimed to enhance the solubility and dissolution of EMS employing solid dispersion (SD) formulated from two grades of poly ethylene glycol (PEG) polymers (i.e. PEG 3350 & PEG 6000 Da) either individually or in combination with Tween 80.
MATERIALS AND METHODS
ESM SDs were prepared by solvent evaporation method using either PEG 3350 or PEG 6000 at various (drug: polymer, w/w) ratios 1:1, 1:2, 1:3, 1:4, 1:5 alone or combined with Tween 80 added at fixed percentage of 0.1 of drug by weight?. Physical mixtures (PMs) of drug and carriers were also prepared at same ratios. Drug solid dispersions and physical mixtures were characterized in terms of drug content, drug dissolution using dissolution apparatus USP II and assayed using HPLC method. Drug dissolution enhancement ratio (ER %) from SD in comparison to the plain drug was calculated. Drug-polymer interactions were evaluated using Differential Scanning Calorimetry (DSC) and FT-IR.
RESULTS AND DISCUSSION
The in vitro solubility and dissolution studies showed SDs prepared using both polymers produced a remarkable improvement (p<0.05) in comparison to the plain drug which reached around 32% (Fig. 1). The dissolution enhancement ratio was polymer type and concentration-dependent. Adding Tween 80 to the SD did not show further dissolution enhancement but reduced the required amount of the polymer to get the same dissolution enhancement. The DSC and FT-IR studies indicated that using SD resulted in transformation of drug from crystalline to amorphous form.
CONCLUSIONS
This study indicated that SDs prepared by using both polymers i.e. PEG 3350 and PEG 6000 improved the in-vitro solubility and dissolution of ESM remarkably which may result in improving the drug bioavailability in vivo.
Acknowledgments
This work is a part of MSc thesis of O.M. Ali at the Faculty of Pharmacy, Aleppo University, Syria.
REFERENCES
[1] Ruilope L, Jager B: Eprosartan for the treatment of hypertension. Expert Opin Pharmacother 2003; 4(1):107-14
[2] Tenero D, Martin D, Wilson B, Jushchyshyn J, Boike S, Lundberg, D, et al. Pharmacokinetics of intravenously and orally administered Eprosartan in healthy males: absolute bioavailability and effect of food. Biopharm Drug Dispos 1998; 19(6): 351- 6.