Shape optimisation using Computational Fluid Dynamics and Evolutionary Algorithms

This is the author accepted manuscript.Optimisation of designs using Computational Fluid Dynamics (CFD) are frequently performed across many fields of research, such as the optimisation of an aircraft wing to reduce drag, or to increase the efficiency of a heat exchanger. General optimisation strategies involves altering design variables with a view to improve appropriate objective function(s). Often the objective function(s) are non-linear and multi-modal, and thus polynomial time algorithms for solving such problems may not be available. In such cases, applying Evolutionary Algorithms (EAs - a class of stochastic global optimisation techniques inspired from natural evolution) may locate good solutions within a practical time frame. The traditional CFD design optimisation process is often based on a ‘trial-and-error type approach. Starting from an initial geometry, Computational Aided Design changes are introduced manually based on results from a limited number of design iterations and CFD analyses. The process is usually complex, time-consuming and relies heavily on engineering experience, thus making the overall design procedure inconsistent, i.e. different ‘best’ solutions are obtained from different designers. [...]This work was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) grant (reference number: EP/M017915/1) for the University of Exeter’s College of Engineering, Mathematics, and Physical Sciences

Automatic shape optimisation of the turbine-99 draft tube

This is the author accepted manuscript.INTRODUCTION The performance of a hydraulic reaction turbine is significantly affected by the efficiency of its draft tube. Factors which impede the tube’s performance include the geometrical shape (profile), and velocity distribution at the inflow. So far, the design of draft tubes has been improved through experimental observations resulting in empirical formulae or ‘rules of thumb’. The use of Computational Fluid Dynamics (CFD) in this design process has only been a recent addition due to its robustness and cost-effectivenesses with increasing availability to computational power. The flexibility of CFD, allowing for comprehensive analysis of complex profiles, is especially appealing for optimising the design. Hence, there is a need for developing an accurate and reliable CFD approach together with an efficient optimisation strategy. Flows through a turbine draft tube are characterised as turbulent with a range of flow phenomena, e.g. unsteadiness, flow separation, and swirling flow. With the aim of improving the techniques for analysing such flows, the turbomachinery community have proposed a standard test case in the form of the Turbine-99 draft tube [1]. Along with this standard geometry, with the aim of simulating the swirling inflow, an additional runner proposed by Cervantes [2] is included in the present work. The draft tube geometry is shown in Fig.1. The purpose of this abstract is to outline the framework developed to achieve the automated shape optimisation of this draft tube.This work was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) grant (reference number: EP/M017915/1) for the University of Exeters College of Engineering, Mathematics, and Physical Sciences

Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation

This is the author accepted manuscript. The final version is available from ACM via the DOI in this recordThe performance of acquisition functions for Bayesian optimisation is investigated in terms of the Pareto front between exploration and exploitation. We show that Expected Improvement and the Upper Confidence Bound always select solutions to be expensively evaluated on the Pareto front, but Probability of Improvement is never guaranteed to do so and Weighted Expected Improvement does only for a restricted range of weights. We introduce two novel -greedy acquisition functions. Extensive empirical evaluation of these together with random search, purely exploratory and purely exploitative search on 10 benchmark problems in 1 to 10 dimensions shows that -greedy algorithms are generally at least as effective as conventional acquisition functions, particularly with a limited budget. In higher dimensions -greedy approaches are shown to have improved performance over conventional approaches. These results are borne out on a real world computational fluid dynamics optimisation problem and a robotics active learning problem.Innovate U

Fixed Versus Variable Dosing of Prothrombin Complex Concentrate for Bleeding Complications of Vitamin K Antagonists:The PROPER3 Randomized Clinical Trial

STUDY OBJECTIVE: To determine if a fixed dose of 1000 IU of 4-factor prothrombin complex concentrate (4F-PCC) is as effective as traditional variable dosing based on body weight and international normalized ratio (INR) for reversal of vitamin K antagonist (VKA) anticoagulation. METHODS: In this open-label, multicenter, randomized clinical trial, patients with nonintracranial bleeds requiring VKA reversal with 4F-PCC were allocated to either a 1,000-IU fixed dose of 4F-PCC or the variable dose. The primary outcome was the proportion of patients with effective hemostasis according to the International Society of Thrombosis and Haemostasis definition. The design was noninferiority with a lower 95% confidence interval of no more than -6%. When estimating sample size, we assumed that fixed dosing would be 4% superior. RESULTS: From October 2015 until January 2020, 199 of 310 intended patients were included before study termination due to decreasing enrollment rates. Of the 199 patients, 159 were allowed in the per-protocol analysis. Effective hemostasis was achieved in 87.3% (n=69 of 79) in fixed compared to 89.9% (n=71 of 79) in the variable dosing cohort (risk difference 2.5%, 95% confidence interval -13.3 to 7.9%, P=.27). Median door-to-needle times were 109 minutes (range 16 to 796) in fixed and 142 (17 to 1076) for the variable dose (P=.027). INR less than 2.0 at 60 minutes after 4F-PCC infusion was reached in 91.2% versus 91.7% (P=1.0). CONCLUSION: The large majority of patients had good clinical outcome after 4F-PCC use; however, noninferiority of the fixed dose could not be demonstrated because the design assumed the fixed dose would be 4% superior. Door-to-needle time was shortened with the fixed dose, and INR reduction was similar in both dosing regimens

Design implications for task-specific search utilities for retrieval and re-engineering of code

The importance of information retrieval systems is unquestionable in the modern society and both individuals as well as enterprises recognise the benefits of being able to find information effectively. Current code-focused information retrieval systems such as Google Code Search, Codeplex or Koders produce results based on specific keywords. However, these systems do not take into account developers’ context such as development language, technology framework, goal of the project, project complexity and developer’s domain expertise. They also impose additional cognitive burden on users in switching between different interfaces and clicking through to find the relevant code. Hence, they are not used by software developers. In this paper, we discuss how software engineers interact with information and general-purpose information retrieval systems (e.g. Google, Yahoo!) and investigate to what extent domain-specific search and recommendation utilities can be developed in order to support their work-related activities. In order to investigate this, we conducted a user study and found that software engineers followed many identifiable and repeatable work tasks and behaviours. These behaviours can be used to develop implicit relevance feedback-based systems based on the observed retention actions. Moreover, we discuss the implications for the development of task-specific search and collaborative recommendation utilities embedded with the Google standard search engine and Microsoft IntelliSense for retrieval and re-engineering of code. Based on implicit relevance feedback, we have implemented a prototype of the proposed collaborative recommendation system, which was evaluated in a controlled environment simulating the real-world situation of professional software engineers. The evaluation has achieved promising initial results on the precision and recall performance of the system

Stress degradation studies and development of stability-indicating TLC-densitometry method for determination of prednisolone acetate and chloramphenicol in their individual and combined pharmaceutical formulations

A rapid and reproducible stability indicating TLC method was developed for the determination of prednisolone acetate and chloramphenicol in presence of their degraded products. Uniform degradation conditions were maintained by refluxing sixteen reaction mixtures for two hours at 80°C using parallel synthesizer including acidic, alkaline and neutral hydrolysis, oxidation and wet heating degradation. Oxidation at room temperature, photochemical and dry heating degradation studies were also carried out. Separation was done on TLC glass plates, pre-coated with silica gel 60F-254 using chloroform: methanol (14:1 v/v). Spots at Rf 0.21 ± 0.02 and Rf 0.41 ± 0.03 were recognized as chloramphenicol and prednisolone acetate, respectively. Quantitative analysis was done through densitometric measurements at multiwavelength (243 nm, λmax of prednisolone acetate and 278 nm, λmax of chloramphenicol), simultaneously. The developed method was optimized and validated as per ICH guidelines. Method was found linear over the concentration range of 200-6000 ng/spot with the correlation coefficient (r2 ± S.D.) of 0.9976 ± 3.5 and 0.9920 ± 2.5 for prednisolone acetate and chloramphenicol, respectively. The developed TLC method can be applied for routine analysis of prednisolone acetate and chloramphenicol in presence of their degraded products in their individual and combined pharmaceutical formulations

Trading-off Data Fit and Complexity in Training Gaussian Processes with Multiple Kernels

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this recordLOD 2019: Fifth International Conference on Machine Learning, Optimization, and Data Science, 10-13 September 2019, Siena, ItalyGaussian processes (GPs) belong to a class of probabilistic techniques that have been successfully used in different domains of machine learning and optimization. They are popular because they provide uncertainties in predictions, which sets them apart from other modelling methods providing only point predictions. The uncertainty is particularly useful for decision making as we can gauge how reliable a prediction is. One of the fundamental challenges in using GPs is that the efficacy of a model is conferred by selecting an appropriate kernel and the associated hyperparameter values for a given problem. Furthermore, the training of GPs, that is optimizing the hyperparameters using a data set is traditionally performed using a cost function that is a weighted sum of data fit and model complexity, and the underlying trade-off is completely ignored. Addressing these challenges and shortcomings, in this article, we propose the following automated training scheme. Firstly, we use a weighted product of multiple kernels with a view to relieve the users from choosing an appropriate kernel for the problem at hand without any domain specific knowledge. Secondly, for the first time, we modify GP training by using a multi-objective optimizer to tune the hyperparameters and weights of multiple kernels and extract an approximation of the complete trade-off front between data-fit and model complexity. We then propose to use a novel solution selection strategy based on mean standardized log loss (MSLL) to select a solution from the estimated trade-off front and finalise training of a GP model. The results on three data sets and comparison with the standard approach clearly show the potential benefit of the proposed approach of using multi-objective optimization with multiple kernels.Natural Environment Research Council (NERC

Do critical thinkers drink too much alcohol, forget to do class assignments, or cheat on exams? Using a critical thinking measure to predict college students’ real-world outcomes

Critical thinking is a higher-order way of reasoning composed of the skill and will to use cognitive abilities and knowledge on a daily basis. It is identified as essential by higher education institutions, corporations, and society in general. To analyze whether college students are critical thinkers in their daily lives, the Halpern Critical Thinking Assessment (HCTA; Halpern in Halpern Critical Thinking Assessment (Measurement instrument), Schuhfried, Mödling, 2012) and the real-world outcomes inventory (RWO; Butler in Appl Cogn Psychol 26(5):721–729, 2012) were administered to 238 students. We performed a cluster analysis (K-means-constrained clustering method), and ANOVAs for each cluster solution tested to identify the most suitable clustering solution, taking the RWO inventory dimensions as dependent variables and cluster membership as an independent variable. Four separate clusters emerged, each representing a different profile related to students’ everyday negative outcomes resulting from a lack of critical thinking. We performed multinomial logistic regression to examine which dimensions of the HCTA test, as well as gender, age, and disciplinary area, predicted the four singular groups of students that emerged: “Mature,” “Risk-taking,” “Lost in translation,” and “Reflective.” Results indicate that: (1) age is a relevant predictor of slackness, rashness, and health neglect, all characteristics of “Mature” students; (2) students who are particularly skilled in hypothesis testing tend to be “Risk-taking,” while it is less likely that students who are specifically competent in argument analysis will be in this group; (3) gender is relevant to predict “Lost in translation” students, while argument analysis is negatively related to the chances of being in this group. Our study supports the relevance of critical thinking in daily decisions and everyday outcomes.FCT -Fundação para a Ciência e a Tecnologia(Advanced Training)info:eu-repo/semantics/publishedVersio