Energy consideration in machining operations - towards explanatory models for optimisation results

Part of: Seliger, Günther (Ed.): Innovative solutions : proceedings / 11th Global Conference on Sustainable Manufacturing, Berlin, Germany, 23rd - 25th September, 2013. - Berlin: Universitätsverlag der TU Berlin, 2013. - ISBN 978-3-7983-2609-5 (online). - http://nbn-resolving.de/urn:nbn:de:kobv:83-opus4-40276. - pp. 153–158.This paper reports the application of a systematic research methodology for uncovering the reasons behind results obtained when energy is considered in machining optimisation. A direct search optimisation method was used as a numerical experimentation rig to investigate the reasoning behind the results obtained in applying Taguchi methods and Genetic algorithm (GA). Representative data was extracted from validated machining science equations and studied using graphical multivariate data analysis. The results showed that over 80% of reduction in energy consumption could be achieved over the recommendations from machining handbooks. It was shown that energy was non-conflicting with the cost and time, but conflicting with quality factors such as surface roughness and technical factors such as power requirement and cutting force. These characteristics of the solutions can provide an explanative motif required for practitioners to trust and use the optimisation results

The reversal effects of Irvingia gabonensis seed extract on ethanol-induced hypertension in male Wistar rats

Irvingia gabonensis (Aubry-Lecomte ex O'Rorke) Baill is a tropical African tree widely used for the treatment of deranged body weight, blood sugar, and blood cholesterol in China, India, and Africa. Despite its medicinal uses, there is no documented report on its role and mechanism of action in the management of hypertension. In this study, we investigated the reversal effects of n-hexane extract (oil) of Irvingia gabonensis seed on ethanol-induced hypertension in male Wistar rats. Twenty-five (25) male Wistar rats were randomly assigned into five groups. Group A (control) received normal saline (10 mL/kg) orally, while groups B to E received 5% ethanol (10 mL/kg) alone daily for 14 consecutive days to induce hypertension. Thereafter, oral administration of Irvingia gabonensis at 250 mg/kg/day, 500 mg/kg/day, and enalapril at 0.1 mg/kg was introduced from day 15 to 35 in groups C to E, respectively. The results showed that ethanol caused a significant increase in diastolic blood pressure (DBP), systolic blood pressure (SBP), mean arterial blood pressure (MABP), heart rate (HR), and a reduction in mean weight gain in normotensive rats. However, treatment with n-hexane extract (oil) of the seed of Irvingia gabonensis or enalapril showed a significant (P=0.001) reversal in SBP, DBP, MABP, HR, and body weight gain compared to the ethanol-induced hypertensive rats. The study showed that Irvingia gabonensis seed oil administered at 250 mg/kg has a potency similar to enalapril in reducing blood pressure and heart rate and reversing weight loss in ethanol-induced hypertension. Also, it reversed the deleterious effects of ethanol on the architecture of the cardiac and renal tissues. The reversal effect of Irvingia gabonensis oil on hypertension was attributed to its antihypertensive and cytoprotective effects, resulting from the potent oil fingerprint of the extract

A Framework for Improving the Sharing of Manufacturing Knowledge through Micro-Blogging

The purpose of this paper is to report on an industrial investigation, conducted within a leading power generation manufacturer, to better understand the organisational processes and challenges present in relation to the management and sharing of knowledge during product manufacturing. Findings reveal that the organisation is failing to fully benefit from web 2.0 technologies and particularly micro-blogging. Details of the investigation results are presented and a conceptual framework is proposed to demonstrate how organisations may enhance the sharing of explicit manufacturing knowledge using micro-blogging tools

Investigation of Temperature Distribution in a Slab Using Lattice Boltzmann Method

In this paper, the temperature distribution in a slab was investigated. A model based on the Boltzmann transport equation without heat source was simplified using the Bhatnagar-Gross-Krook (BGK) approximation was applied. This is an example of the Lattice Boltzmann Method. The model was developed based on using a D2Q4 lattice arrangement for the medium of study. To obtain results, the model was tested on different cases: Two box-shaped slabs with different boundary conditions, and a T-shaped and an L-shaped slabs to determine the temperature distributions different times t > 0. The results obtained based on the developed model were validated with the enterprise software COMSOL Multiphysics which is based on the Finite Element Method. For the two cases of box-shaped and the T-shaped slabs, their results were in nearly perfect agreement with the finite element method. However, for the L-shaped slab, there was good agreement at most points apart from the regions where there was change of shape. In conclusion there is high agreement between the results of LBM and using COMSOL, which proves that LBM can be used to determine temperature distribution in a slab accurately

AfriQA:Cross-lingual Open-Retrieval Question Answering for African Languages

African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users. Cross-lingual open-retrieval question answering (XOR QA) systems -- those that retrieve answer content from other languages while serving people in their native language -- offer a means of filling this gap. To this end, we create AfriQA, the first cross-lingual QA dataset with a focus on African languages. AfriQA includes 12,000+ XOR QA examples across 10 African languages. While previous datasets have focused primarily on languages where cross-lingual QA augments coverage from the target language, AfriQA focuses on languages where cross-lingual answer content is the only high-coverage source of answer content. Because of this, we argue that African languages are one of the most important and realistic use cases for XOR QA. Our experiments demonstrate the poor performance of automatic translation and multilingual retrieval methods. Overall, AfriQA proves challenging for state-of-the-art QA models. We hope that the dataset enables the development of more equitable QA technology