RC column strengthening by lateral pre-tensioning of FRP

This paper presents a unique strengthening technique for existing concrete columns that use expansive materials to apply lateral pre-tensioning. The technique increases the capacity and ductility of a column as well as achieving better utilisation of the confining FRP (Fibre Reinforced Polymer) material. The confinement material properties and the confined cylinder performance are investigated experimentally. From the results, it is shown that it is possible to control the degree of applied pre-tension by controlling the amount of expansive material used. In addition, it is confirmed that jacketing columns by pre-tensioned FRP materials can increase the load bearing capacity up to 35% compared with no pre-tensioning and up to more than four times compared with unconfined concrete. The paper presents details of experimental work undertaken for the development of the confinement pressure with different confining materials (Carbon-CFRP, Glass-GFRP and Steel) and makes comparisons with predictive models

Concrete beams with externally bonded flexural FRP-reinforcement: analytical investigation of debonding failure

This paper studies the problem of early concrete cover delamination and plate-end failure of reinforced concrete beams strengthened with externally bonded FRP-reinforcement. The accuracy of analytical models and finite element (FE) methods for predicting this type of failure is assessed against published experimental data. Two design approaches based on the maximum concrete tensile strength and the shear capacity of concrete beams were examined first and it was found that linear elastic analysis cannot accurately predict the brittle plate-end concrete failure. It was also found that the extent of strengthening that can be achieved is limited by the shear capacity of concrete beams. The FE analysis is used to examine the effects of internal tensile reinforcement on the magnitude of principal tensile stresses in the critical region. The non-linear behaviour of FRP-strengthened beams is also examined in the FE analysis using the smeared crack model for concrete which is shown to adequately display the inelastic deformation of the beam. Finally, the mixed mode of failure due to the combined shear and concrete cover delamination is addressed through modelling plate-end and shear crack discontinuities using the discrete crack approach

Axial behaviour of prestressed high strength steel tubular members

The axial behaviour of high strength steel tubular elements with internal prestress-ing cables, representing the chord members in prestressed trusses, is investigated herein. Ex-periments on tensile and compressive members were carried out, with the key variables exam-ined being the steel grade (S460 and S690), the initial prestress level and the presence of grout. FE models were developed to replicate the experiments and generate parametric results. The presence of cables was shown to enhance the tensile load-carrying capacity of the mem-bers while the application of prestress extended the elastic range. In compression, prestressing was detrimental, and a modified Perry-Robertson design approach was examined

Seismic retrofit schemes for RC structures and local-global consequences

A review of repair schemes for reinforced concrete frame buildings is presented in this paper, within the context of global objectives of the intervention process. Local as well as global intervention measures are discussed and their technological application details outlined. The effect of the reviewed repair schemes on the member, sub‐assemblage and system performance are qualitatively assessed. The important role of the foundation system in the rehabilitation process is outlined and measures that are consistent with the super‐structure intervention methods are given. The paper concludes with a global assessment of the effect of repair methods on stiffness, strength and ductility, the three most important seismic response parameters, to assist researchers and practitioners in decision‐making to satisfy their respective intervention objectives. The framework for the paper complies with the requirements of consequence‐based Engineering, where the expected damage is addressed only when consequences are higher than acceptable consequences, and a cyclical process of assessment and re‐assessment is undertaken until the community objectives are deemed to be satisfied

Field Dependent/Independent Learning Strategies and the Knowledge of the Musical Notes

Abstract The field dependence/independence (FD/I) construct is among the most widely studied areas in the range of cognitive style dimensions appearing in the language learning literature. FD/I concerns two contrasting ways of processing information. This research aims to investigate the possibility of any significant relationships between the field dependent/independent learning strategy and having the knowledge of musical notes. It wants to show that if a person knows the musical notes what kind of person he is in terms of FD/I learning strategies. The first part is the Introduction, the second part deals with methodology and discussion, part three deals with the results and in the last part some conclusion is drawn

AI-enabled dynamic capabilities for transforming digital business models to smart business models

Abstract AI as the most important general-purpose technology of the day with its innumerable possibilities is on its way to become a key technology for the digital transformation. Algorithms especially for ML usually perform various tasks outstandingly. Hybrid models of AI, if put into business models, would help in improving the match making between actors of the ecosystems. However, many aspiring digital platforms lack effective strategies to establish profitable digital business models. Emerging digital healthcare market is shifting from traditional hospital-centric care to a more virtual, and personalized care that heavily leverages the latest technologies around AI, DL, DA, genomics, home-based healthcare, robotics, and three-dimensional printing of tissue and implants. This emerging digital healthcare market requires a profound, yet little understood perspective of transformation of digital business model by identifying the AI-enabled dynamic capabilities that could serve as a strong competitive differentiator. This understanding would help in value capture and value creation for companies who are developing digital platform to pull insights from data, and secure competitive advantage. The aim of this dissertation is to identify the AI-enabled dynamic capabilities that companies need for the transformation of their digital business models to smart business models in the emerging digital healthcare market. The findings of the study reveal that orchestration as one of the AI-enabled dynamic capabilities could be categorized as Capability to install desired information behaviors and values, Leadership capabilities, Capability to develop appropriate information management processes, and Information analytics capabilities. Also, these dynamic capabilities could be categorized as assisting, augmenting, and automating meaning that taking specific orchestrator roles (e.g., operational role implementation or role switching, role augmentation, and role automation). These three important observations are aligned with the preceding discussions in the literatures and utilizing them would explicate how different types of dynamic capabilities allow orchestrators to adopt different roles and succeed in conducting the focal activities of a company. However, the goal of this study is not to integrate or bridge specific paradigms, but to identify the AI-enabled dynamic capabilities. So, this dissertation further argues and conclude that the digital business model is a higher-level strategic AI-enabled dynamic capability that can serve as a tool for sensing, seizing, and transforming in the company business ecosystems through opportunity exploration and exploitation, value creation and capture, advantage exploration and exploitation functions to respond to the company’s digital business model transformation. Businesses can move along these two identified AI-enabled dynamic capabilities (digital business model itself and orchestration) for the transformation of their current digital business models from AI perspective and target smart business model vision in the emerging digital healthcare market. Effective and efficient implementation of AI in the transformation of the companies’ digital business models would enhance the competitiveness of many businesses. However, it won’t help some other businesses drive value, opportunity, and advantage by improving the process through automation to win the market. In most cases, AI augments rather than replacing the human effort.Tiivistelmä Tekoäly on nykypäivän tärkeimpiä yleiskäyttöisiä teknologioita ja sen lukemattomat mahdollisuudet ovat tulossa digitaalisen muutoksen avaintekijöiksi. Esimerkiksi koneoppimiseen tarkoitetut algoritmit suorittavat jo merkittäviä tehtäviä. Tekoälyn hybridimallit, jos ne yhdistetään liiketoimintamalleihin, auttavat parantamaan liiketoimintaekosysteemin toimijoiden yhteensovittamista. Monilta kehittyviltä digitaalisilta alustoilta puuttuu kuitenkin tehokkaita strategioita tekoälyperustaisten digitaalisten liiketoimintamallien luomiseksi. Sellaiset markkinat kuin terveydenhuolto ovat avautumassa ja siirtymässä perinteisestä sairaalakeskeisestä toiminnasta virtuaalisempaan ja yksilöllisempään suuntaan, pyrkien hyödyntämään uusinta teknologiaa juuri tekoälyn mutta myös syväoppimisen, data-analytiikan, genomiikan, kotihoidon, robotiikan ja kolmiulotteisen kudosten ja implanttien tulostuksen muodossa. Nämä markkinat edellyttävät syvällistä mutta vielä vähän ymmärrettyä ja kokonaisvaltaista näkökulmaa älykkäiden liiketoimintamallien omaksumiseen. Tämä edellyttää, että tunnistetaan ne tärkeimmät dynaamiset kyvykkyydet, jotka voivat toimia vahvoina kilpailutekijöinä yrityksille, jotka kehittävät digitaalisia alustoja saadakseen sekä näkemyksiä datasta että turvatakseen kilpailuetunsa. Tämän tutkimuksen tavoitteena onkin tunnistaa kyvykkyydet, joita yritykset tarvitsevat muuttaakseen digitaalisia liiketoimintamallejaan älykkäiksi terveydenhuollon markkinoilla. Tutkimuksen tulokset osoittavat, että liiketoimintaekosysteemien orkestrointi on yksi tärkeimmistä tällaisista kyvykkyyksistä. Se voidaan hahmottaa kyvyksi ohjata tietokäyttäytymistä ja arvoja, johtamiskyvykkyyksiksi ja kyvyksi kehittää tarpeellisia tiedonhallintaprosesseja ja tiedon analysointikeinoja. Kyvykkyydet voitaisiin myös luokitella avustaviksi, täydentäviksi ja automatisoiviksi, mikä tarkoittaa esimerkiksi tiettyjen orkestrointiroolien ottamista ja toteuttamista tai roolin vaihtoa, lisäystä ja automatisointia. Tämä on hyvin linjassa aiemmissa tutkimuksissa esitettyjen johtopäätösten kanssa, mutta kyvykkyyksiin paneutuminen selventää, miten ne mahdollistavat orkestroijien erilaiset roolit ja onnistumisen niissä. Tutkimuksen tavoitteena ei kuitenkaan ole uppoutua tiettyihin rooleihin, vaan tunnistaa tekoälyn mahdollistamat kyvykkyydet digitaalisen liiketoimintamallin muutoksessa älykkääksi liiketoimintamalliksi. Tutkimuksessa päätellään, että älykäs liiketoimintamalli on yrityksen korkean tason strateginen kyvykkyys. Se voi toimia keinona liiketoimintapotentiaalin havaitsemiseen, sellaiseen tarttumiseen ja liiketoiminnan muuttamiseen niin, että mahdollisuudet hyödynnetään arvon luomiseksi ja nauttimiseksi. Yritykset voivat älykkään liiketoimintamallin ja ekosysteemisen orkestrointikyvykkyytensä avulla kehittää vision pärjätäkseen muuttuvilla terveydenhuollon markkinoilla. Vaikka älykäs liiketoimintamalli parantaisi monen yrityksen kilpailukykyä, se ei kuitenkaan mahdollisesti auta aivan kaikkia luomaan mahdollisuuksia ja arvoa ja tuottamaan uusia automatisoituja prosesseja. Useimmissa tapauksissa tekoäly lisäksi täydentää ihmisen työtä sen sijaan, että se korvaisi työn tekemisen kokonaan