5,277 research outputs found
Endogenous measures for contextualising large-scale social phenomena: a corpus-based method for mediated public discourse
This work presents an interdisciplinary methodology for developing endogenous measures of group membership through analysis of pervasive linguistic patterns in public discourse. Focusing on political discourse, this work critiques the conventional approach to the study of political participation, which is premised on decontextualised, exogenous measures to characterise groups. Considering the theoretical and empirical weaknesses of decontextualised approaches to large-scale social phenomena, this work suggests that contextualisation using endogenous measures might provide a complementary perspective to mitigate such weaknesses.
This work develops a sociomaterial perspective on political participation in mediated discourse as affiliatory action performed through language. While the affiliatory function of language is often performed consciously (such as statements of identity), this work is concerned with unconscious features (such as patterns in lexis and grammar). This work argues that pervasive patterns in such features that emerge through socialisation are resistant to change and manipulation, and thus might serve as endogenous measures of sociopolitical contexts, and thus of groups.
In terms of method, the work takes a corpus-based approach to the analysis of data from the Twitter messaging service whereby patterns in usersâ speech are examined statistically in order to trace potential community membership. The method is applied in the US state of Michigan during the second half of 2018â6 November having been the date of midterm (i.e. non-Presidential) elections in the United States. The corpus is assembled from the original posts of 5,889 users, who are nominally geolocalised to 417 municipalities. These users are clustered according to pervasive language features. Comparing the linguistic clusters according to the municipalities they represent finds that there are regular sociodemographic differentials across clusters. This is understood as an indication of social structure, suggesting that endogenous measures derived from pervasive patterns in language may indeed offer a complementary, contextualised perspective on large-scale social phenomena
Animating potential for intensities and becoming in writing: challenging discursively constructed structures and writing conventions in academia through the use of storying and other post qualitative inquiries
Written for everyone ever denied the opportunity of fulfilling their academic potential, this is âChloeâs storyâ. Using composite selves, a phrase chosen to indicate multiplicities and movement, to story both the initial event leading to âChloeâsâ immediate withdrawal from a Further Education college and an imaginary second chance to support her whilst at university, this Deleuzo-Guattarian (2015a) âassemblageâ of post qualitative inquiries offers challenge to discursively constructed structures and writing conventions in academia. Adopting a posthuman approach to theorising to shift attention towards affects and intensities always relationally in action in multiple âassemblagesâ, these inquiries aim to decentre individual âlecturerâ and âstudentâ identities. Illuminating movements and moments quivering with potential for change, then, hoping thereby to generate second chances for all, different approaches to writing are exemplified which trouble those academic constraints by fostering inquiry and speculation: moving away from âwhat isâ towards âwhat ifâ.
With the formatting of this thesis itself also always troubling the rigid Deleuzo-Guattarian (2015a) âsegmentary linesâ structuring orthodox academic practice, imbricated in these inquiries are attempts to exemplify Manningâs (2015; 2016) âartfulnessâ through shifts in thinking within and around an emerging PhD thesis. As writing resists organising, the verb thesisising comes into play to describe the processes involved in creating this always-moving thesis. Using âlanding sitesâ (Arakawa and Gins, 2009) as a landscaping device, freely creating emerging âlines of flightâ (Deleuze and Guattari, 2015a) so often denied to students forced to adhere to strict academic conventions, this âmovement-movingâ (Manning, 2014) opens up opportunities for change as in Manningâs (2016) âresearch-creationâ. Arguing for a moving away from writing-representing towards writing-inquiring, towards a writing âthat doesâ (Wyatt and Gale, 2018: 127), and toward writing as immanent doing, it is hoped to animate potential for intensities and becoming in writing, offering opportunities and glimmerings of the not-yet-known
Coding Christianity: Negotiating Religious Dialogue in Online Participatory Spaces
This dissertation examines rhetorical conditions and internet-mediated communication strategies that open and close dialogue between individuals with diverse and conflicting worldviews. The author illustrates this tension through sacred-secular interactions in college composition classrooms and online environments, positing that navigating conflict between these discoursesânamely those espoused by religiously committed students and public university instructorsâoften requires stepping outside of adversarial communication frameworks. This project makes a case for models of civic engagement that use more deliberative rhetorical approaches prioritizing empathy over defensiveness and understanding before persuasion. To develop these non-adversarial communication approaches for the composition classroom, the author looks to participatory media for insights and studies the negotiation strategies of Christian and atheist YouTube users who leverage the affordances of the video medium, internet logics, and invitational rhetorical strategies to engage ideological differences in their respective online communities. Through mixed methods research involving in-depth interviews with five YouTube vloggers, netnographic study of over 3,000 videos, and statistical analysis of 76,000+ user comments, Coding Christianity finds that perspective-taking in conflict-ridden environments can happen between netizens when content creators opt out of âflame warsâ and, instead, explicitly model critical openness and charitable listening to perceived âothers.â The author ultimately suggests that sacred-secular tension in both academic and digital environments be used, not diffused, to negotiate conflicting values and engage in rigorous, civil dialogues
Deposição de filmes do diamante para dispositivos electrónicos
This PhD thesis presents details about the usage of diamond in electronics. It presents a review of the properties of diamond and the mechanisms of its growth using hot filament chemical vapour deposition (HFCVD). Presented in the thesis are the experimental details and discussions that follow from it about the optimization of the deposition technique and the growth of diamond on various electronically relevant substrates. The discussions present an analysis of the parameters typically involved in the HFCVD, particularly the pre-treatment that the substrates receive- namely, the novel nucleation procedure (NNP), as well as growth temperatures and plasma chemistry and how they affect the characteristics of the thus-grown films. Extensive morphological and spectroscopic analysis has been made in order to characterise these films.Este trabalho discute a utilização de diamante em aplicaçÔes electrĂłnicas. Ă apresentada uma revisĂŁo detalhada das propriedades de diamante e dos respectivos mecanismos de crescimento utilizando deposição quĂmica a partir da fase vapor com filament quente (hot filament chemical vapour deposition - HFCVD). Os detalhes experimentais relativos Ă otimização desta tĂ©cnica tendo em vista o crescimento de diamante em vĂĄrios substratos com relevĂąncia em eletrĂłnica sĂŁo apresentados e discutidos com detalhe. A discussĂŁo inclui a anĂĄlise dos parĂąmetros tipicamente envolvidos em HFCVD, em particular do prĂ©-tratamento que o substrato recebe e que Ă© conhecido na literatura como "novel nucleation procedure" (NNP), assim como das temperaturas de crescimento e da quĂmica do plasma, bem como a influĂȘncia de todos estes parĂąmetros nas caracterĂsticas finais dos filmes. A caracterização morfolĂłgica dos filmes envolveu tĂ©cnicas de microscopia e espetroscopia.Programa Doutoral em Engenharia EletrotĂ©cnic
Optimización del rendimiento y la eficiencia energética en sistemas masivamente paralelos
RESUMEN Los sistemas heterogéneos son cada vez mås relevantes, debido a sus capacidades de rendimiento y eficiencia energética, estando presentes en todo tipo de plataformas de cómputo, desde dispositivos embebidos y servidores, hasta nodos HPC de grandes centros de datos. Su complejidad hace que sean habitualmente usados bajo el paradigma de tareas y el modelo de programación host-device. Esto penaliza fuertemente el aprovechamiento de los aceleradores y el consumo energético del sistema, ademås de dificultar la adaptación de las aplicaciones.
La co-ejecuciĂłn permite que todos los dispositivos cooperen para computar el mismo problema, consumiendo menos tiempo y energĂa. No obstante, los programadores deben encargarse de toda la gestiĂłn de los dispositivos, la distribuciĂłn de la carga y la portabilidad del cĂłdigo entre sistemas, complicando notablemente su programaciĂłn.
Esta tesis ofrece contribuciones para mejorar el rendimiento y la eficiencia energética en estos sistemas masivamente paralelos. Se realizan propuestas que abordan objetivos generalmente contrapuestos: se mejora la usabilidad y la programabilidad, a la vez que se garantiza una mayor abstracción y extensibilidad del sistema, y al mismo tiempo se aumenta el rendimiento, la escalabilidad y la eficiencia energética. Para ello, se proponen dos motores de ejecución con enfoques completamente distintos.
EngineCL, centrado en OpenCL y con una API de alto nivel, favorece la mĂĄxima compatibilidad entre todo tipo de dispositivos y proporciona un sistema modular extensible. Su versatilidad permite adaptarlo a entornos para los que no fue concebido, como aplicaciones con ejecuciones restringidas por tiempo o simuladores HPC de dinĂĄmica molecular, como el utilizado en un centro de investigaciĂłn internacional.
Considerando las tendencias industriales y enfatizando la aplicabilidad profesional, CoexecutorRuntime proporciona un sistema flexible centrado en C++/SYCL que dota de soporte a la co-ejecuciĂłn a la tecnologĂa oneAPI. Este runtime acerca a los programadores al dominio del problema, posibilitando la explotaciĂłn de estrategias dinĂĄmicas adaptativas que mejoran la eficiencia en todo tipo de aplicaciones.ABSTRACT Heterogeneous systems are becoming increasingly relevant, due to their performance and energy efficiency capabilities, being present in all types of computing platforms, from embedded devices and servers to HPC nodes in large data centers. Their complexity implies that they are usually used under the task paradigm and the host-device programming model. This strongly penalizes accelerator utilization and system energy consumption, as well as making it difficult to adapt applications.
Co-execution allows all devices to simultaneously compute the same problem, cooperating to consume less time and energy. However, programmers must handle all device management, workload distribution and code portability between systems, significantly complicating their programming.
This thesis offers contributions to improve performance and energy efficiency in these massively parallel systems. The proposals address the following generally conflicting objectives: usability and programmability are improved, while ensuring enhanced system abstraction and extensibility, and at the same time performance, scalability and energy efficiency are increased. To achieve this, two runtime systems with completely different approaches are proposed.
EngineCL, focused on OpenCL and with a high-level API, provides an extensible modular system and favors maximum compatibility between all types of devices. Its versatility allows it to be adapted to environments for which it was not originally designed, including applications with time-constrained executions or molecular dynamics HPC simulators, such as the one used in an international research center.
Considering industrial trends and emphasizing professional applicability, CoexecutorRuntime provides a flexible C++/SYCL-based system that provides co-execution support for oneAPI technology. This runtime brings programmers closer to the problem domain, enabling the exploitation of dynamic adaptive strategies that improve efficiency in all types of applications.Funding: This PhD has been supported by the Spanish Ministry of Education (FPU16/03299 grant),
the Spanish Science and Technology Commission under contracts TIN2016-76635-C2-2-R
and PID2019-105660RB-C22.
This work has also been partially supported by the Mont-Blanc 3: European Scalable and
Power Efficient HPC Platform based on Low-Power Embedded Technology project (G.A. No.
671697) from the European Unionâs Horizon 2020 Research and Innovation Programme
(H2020 Programme). Some activities have also been funded by the Spanish Science and Technology
Commission under contract TIN2016-81840-REDT (CAPAP-H6 network).
The Integration II: Hybrid programming models of Chapter 4 has been partially performed
under the Project HPC-EUROPA3 (INFRAIA-2016-1-730897), with the support of the EC
Research Innovation Action under the H2020 Programme. In particular, the author gratefully
acknowledges the support of the SPMT Department of the High Performance Computing
Center Stuttgart (HLRS)
Data Center Power System Emulation and GaN-Based High-Efficiency Rectifier with Reactive Power Regulation
Data centers are indispensable for today\u27s computing and networking society, which has a considerable power consumption and significant impact on power system. Meanwhile, the average energy usage efficiency of data centers is still not high, leading to significant power loss and system cost.
In this dissertation, effective methods are proposed to investigate the data center load characteristics, improve data center power usage efficiency, and reduce the system cost.
First, a dynamic power model of a typical data center ac power system is proposed, which is complete and able to predict the data center\u27s dynamic performance. Also, a converter-based data center power emulator serving as an all-in-one load is developed. The power emulator has been verified experimentally in a regional network in the HTB. Dynamic performances during voltage sag events and server load variations are emulated and discussed.
Then, a gallium nitride (GaN) based critical conduction mode (CRM) totem-pole power factor correction (PFC) rectifier is designed as the single-phase front-end rectifier to improve the data center power distribution efficiency. Zero voltage switching (ZVS) modulation with ZVS time margin is developed, and a digital variable ON-time control is employed. A hardware prototype of the PFC rectifier is built and demonstrated with high efficiency. To achieve low input current total harmonic distortion (iTHD), current distortion mechanisms are analyzed, and effective solutions for mitigating current distortion are proposed and validated with experiments.
The idea of providing reactive power compensation with the rack-level GaN-based front-end rectifiers is proposed for data centers to reduce data center\u27s power loss and system cost. Full-range ZVS modulation is extended into non-unity PF condition and a GaN-based T-type totem-pole rectifier with reactive power control is proposed. A hardware prototype of the proposed rectifier is built and demonstrated experimentally with high power efficiency and flexible reactive power regulation. Experimental emulation of the whole data center system also validates the capability of reactive power compensation by the front-end rectifiers, which can also generate or consume more reactive power to achieve flexible PF regulation and help support the power system
Methods for integrating machine learning and constrained optimization
In the framework of industrial problems, the application of Constrained Optimization is known to have overall very good modeling capability and performance and stands as one of the most powerful, explored, and exploited tool to address prescriptive tasks. The number of applications is huge, ranging from logistics to transportation, packing, production, telecommunication, scheduling, and much more. The main reason behind this success is to be found in the remarkable effort put in the last decades by the OR community to develop realistic models and devise exact or approximate methods to solve the largest variety of constrained or combinatorial optimization problems, together with the spread of computational power and easily accessible OR software and resources.
On the other hand, the technological advancements lead to a data wealth never seen before and increasingly push towards methods able to extract useful knowledge from them; among the data-driven methods, Machine Learning techniques appear to be one of the most promising, thanks to its successes in domains like Image Recognition, Natural Language Processes and playing games, but also the amount of research involved.
The purpose of the present research is to study how Machine Learning and Constrained Optimization can be used together to achieve systems able to leverage the strengths of both methods: this would open the way to exploiting decades of research on resolution techniques for COPs and constructing models able to adapt and learn from available data.
In the first part of this work, we survey the existing techniques and classify them according to the type, method, or scope of the integration; subsequently, we introduce a novel and general algorithm devised to inject knowledge into learning models through constraints, Moving Target.
In the last part of the thesis, two applications stemming from real-world projects and done in collaboration with Optit will be presented
Recommended from our members
Modality Bridging and Unified Multimodal Understanding
Multimodal understanding is a vast realm of research that covers multiple disciplines. Hence, it requires a correct understanding of the goal in a generic multimodal understanding research study. The definition of modalities of interest is important since each modality requires its own considerations. On the other hand, it is important to understand whether these modalities should be complimentary to each other or have significant overlap in terms of the information they carry. For example, most of the modalities in biological signals do not have significant overlap with each other, yet they can be used together to improve the range and accuracy of diagnoses. An extreme example of two modalities that have significant overlap is an instructional video and its corresponding instructions in detailed texts. In this study, we focus on multimedia, which includes image, video, audio, and text about real world everyday events, mostly focused on human activities.
We narrow our study to the important direction of common space learning since we want to bridge between different modalities using the overlap that a given pair of modalities have.There are multiple applications which require a strong common space to be able to perform desirably. We choose image-text grounding, video-audio autoencoding, video-conditioned text generation, and video-audio-text common space learning for semantic encoding. We examine multiple ideas in each direction and achieve important conclusions. In image-text grounding, we learn that different levels of semantic representations are helpful to achieve a thorough common space that is representative of two modalities. In video-audio autoencoding, we observe that reconstruction objectives can help with a representative common space. Moreover, there is an inherent problem when dealing with multiple modalities at the same time, and that is different levels of granularity. For example, the sampling rate and granularity of video is much higher and more complicated compared to audio. Hence, it might be more helpful to find a more semantically abstracted common space which does not carry redundant details, especially considering the temporal aspect of video and audio modalities. In video-conditioned text generation, we examine the possibility of encoding a video sequence using a Transformer (and later decoding the captions using a Transformer decoder). We further explore the possibility of learning latent states for storing real-world concepts without supervision.
Using the observations from these three directions, we propose a unified pipeline based on the Transformer architecture to examine whether it is possible to train a (true) unified pipeline on raw multimodal data without supervision in an end-to-end fashion. This pipeline eliminates ad-hoc feature extraction methods and is independent of any previously trained network, making it simpler and easier to use. Furthermore, since it only utilizes one architecture, which enables us to move towards even more simplicity. Hence, we take an ambitious step forward and further unify this pipeline by sharing only one backbone among four major modalities: image, video, audio, and text. We show that it is not only possible to achieve this goal, but we further show the inherent benefits of such pipeline. We propose a new research direction under multimodal understanding and that is Unified Multimodal Understanding. This study is the first that examines this idea and further pushes its limit by scaling up to multiple tasks, modalities, and datasets.
In a nutshell, we examine different possibilities for bridging between a pair of modalities in different applications and observe several limitations and propose solutions for them. Using these observations, we provide a unified and strong pipeline for learning a common space which could be used for many applications. We show that our approaches perform desirably and significantly outperform state-of-the-art in different downstream tasks. We set a new baseline with competitive performance for our proposed research direction, Unified Multimodal Understanding
Cybercrime vs Hacktivism: Do we need a differentiated regulatory approach?
Background and aims:
Cybercrime is an issue that increases year on year, however rarely are the motivations behind these attacks investigated. More and more people are turning to the internet to protest with some scholars debating whether hacktivism is a social movement. This Dissertation uses networked social movement theory in order to establish if hacktivism is a social movement or whether it is simply a politically motivated form of cybercrime. While demonstrating hacktivismâs place in the social movement landscape this Dissertation will also analyse how hacktivism is currently regulated and whether the legislative and regulatory tools are appropriate.
Methods:
This Dissertation uses a multi-method approach to establish whether hacktivism could be considered to be a social movement. The first method used is a rhetorical analysis of the Twitter accounts from active hacktivist accounts. Tweets posted by these accounts are coded using Stewartâs functional approach to rhetoric used by social movements (1980) using MAXQDAâs content analysis software. The second method used is a descriptive statistical analysis of a number of publicly available datasets (Zone H; the Cambridge Computer Crime Database; DCMSâs Cyber Security Breaches Surveys from 2017-2021; an AnonOps Internet Relay Chat Channel; a sentiment analysis; the hack aggregator âHackmageddonâ) to establish hacktivismâs similarities and differences to both cybercrime and social movements.
Results and Conclusions::
This Dissertation found that hacktivism is substantially different to cybercrime despite it being regulated as such based on the methods, targets and ideologies. Additionally, the Dissertation found that hacktivism could be considered to be a social movement based on similarities in their communications and motivations as well as the online parallels hacktivism has to social movement methods. The dissertation also found that due to the similarities hacktivism shares with traditional offline protests and hacktivism, the UK should look at the offline parallels when regulating hacktivism to ensure that the human rights of those taking part in hacktivist methods are not being quashed and are being upheld
Recommended from our members
Utilization of date palm tree fibres as biomass resources for developing sustainable composites for industrial applications
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.Petroleum based fibres are dominating our everyday usage of fibres, textiles, and composite development reaching an annual consumption of more than 50 million tons in 2020. Over the years, there has been a desperate need for sustainable alternatives; but unfortunately, the global production of natural fibres (NF) has reached a plateau due to the reliance on very few natural sources and lack of biodiversity. With the growing concern on climate change due to the pollution emitted from petroleum-based manufacturing products and their end life disposal, sustainable manufacturing of sustainable materials represents a primary concern for the construction industry. New technologies and materials are extensively investigated and proposed to meet sustainability guidelines imposed by governments and specifically the United Nations (UN). NF represent one of the most investigated renewable and sustainable materials. The date palm tree (DPT), Phoenix Dactylifera L., produces globally an approximate of 4.8 million tons (dry weight) where 3.6 million tons are produced in the MENA region only as by-products of pruning, regarded as agricultural waste, which are either landfilled or incinerated. This research investigates and develops novel methodologies to overcome the drawbacks of utilizing DPT by-products where DPT fibre (DPF) can be extracted from and utilized as a reinforcement in developing sustainable composites for industrial applications. An intensive literature review database was developed to highlight previous research work and investigations carried out to date on the utilization of DPF and their effect in developing sustainable composites and the drawbacks limiting their feasibility for upscaling and industrialization. This identified the problem statement in current research that must be addressed to distinguish the potential of DPF utilization and industrialization.
Various surface modification treatments as well as their conditions (soaking time and duration) effect on the characteristics of DPF (surface morphology, chemical composition, chemical structure, and crystallinity) was investigated and evaluated to develop a more hydrophobic fibre that enhances the interfacial bonding when used as a reinforcement with various matrix systems (i.e., polymers and cementitious). DPF treated with sodium hydroxide (NaOH) solution, 6%, for 3 hours showed optimal results where an increase in tensile strength of the fibre by 147%. Scanning electron microscopy (SEM) images demonstrated the effectiveness of the surface treatment showing a more porous surface where the impurities and waxes were successfully removed. Furthermore, investigations, evaluation and prediction on the effect of DPF particle size distribution, density, diameter size (unsieved, â„1,000 ÎŒm, 500 â 1,000 ÎŒm, 250 â 500 ÎŒm, 125 â 250 ÎŒm, and â€125 ÎŒm) and loading content (10, 20, 30, 40 wt.% of matrix) on both the mechanical, physical, fungal resistance and disintegration properties of recycled thermoplastic, recycled polyvinyl chloride (RPVC), and biodegradable thermoplastic, polylactic acid (PLA), were evaluated. The hydrophilic nature of DPF contributed to an increase in thickness swelling (TS), moisture content (MC) and water absorption (WA) for both RPVC and PLA reinforced composites. TS, WA and MC increased by 1.57%, 1.76%, and 10.80%, respectively at 40 wt.% DPF loading content when reinforced with RPVC. Moreover, the flexural strength, tensile strength and impact strength decreased as the loading content increased showing maximum reduction at 40 wt.% loading, varying depending on DPF geometry. Furthermore, micromechanics modelling scenarios to predict the fibre orientation was investigated. To determine the effectiveness of DPF orientations in the PLA and RPVC, the rule of mixtures (ROM), modified ROM, inverse rule of mixture (IROM), modified IROM and Halpin-Tsai were applied with three possible fibre orientations in the composites. The modified ROM and modified IROM closely matches the experimental results with the DPF oriented between 0° to 45° in the direction of compression force of the DPF/PLA and DPF/RPVC composites. Also, Composites where exposed to the brown-rot fungus Irpex lacteus and white rot fungus Tyromyces palustris to evaluate its resistance to biodegradation. To evaluate their feasibility to be utilized in the construction sector as a cladding and decking composite which can act as a substitute to wood in developing wood plastic composites (WPC). Composites developed using PLA had higher weight loss (%) when compared to the same samples but reinforced with RPVC. Composites with higher DPF content showed high rates of decay when used with different polymer matrix. Also, DPF length had a significant effect on the disintegration of the composites. DPF/PLA composites did not demonstrate significant weight loss under fungal decay in 8 weeks where the composites with 40 wt.% DPF showed the highest WL% reaching 5.61% and 5.46% when exposed to Tyromyces palustris and Irpex lacteus respectively. Furthermore, a novel investigation on the biodegradation of the samples showed that DPF reinforced PLA can be implemented and developed within a circular economy scheme in which the composite was fully decomposed by earth worm within 6 weeks, developing vermicompost as manure that may be utilized as a nutrient for plants.
Furthermore, an investigation of the processing parameters effect (processing time, temperature, and pressure) on the physical and mechanical properties of DPF reinforced polyester (PES) composite is evaluated. For that, two different temperatures (90 and 110 oC) and three different pressures (1.0, 1.65, and 2.18) MPa which was achieved by varying the load applied (10, 15, and 20) ton and keeping the sample size constant are examined for three different processing durations (3, 6, and 9 min). Results showed that every processing parameter had different effects on the mechanical and physical properties of the composites developed. Moreover, investigations on the effect of varying DPF loading content (1, 2, and 3 wt.% of matrix), and length (10, 20, 30, and 40 mm) of untreated and alkali treated DPF on the mechanical properties of DPF reinforced Ordinary Portland cement (OPC) and DPF reinforced OPC/ground-granulated blast furnace slag (GGBS) were evaluated. Two different curing conditions, water and air, effect on the mechanical strength and physical properties of the composites developed were explored. Results showed that the inclusion of 20 mm treated DPF at a loading content of 1 wt.% with OPC/GGBS as a matrix showed the greatest enhancement in strength by 57.12% and 30.97% of flexural and compressive strength respectively at 28 days of ageing in a water bath. Alkali treatment of DPF demonstrated higher mechanical properties enhancing the optimal mix designsâ mechanical strength by 10% and at 28 days of water curing when compared to the untreated. Moreover, OPC as a pure matrix system had lower mechanical properties where the optimal mix design had an increase in 37.48% and 19.36% on flexural and compressive strength respectively at 28 days of curing in a water bath when compared to OPC/GGBS reinforced composites.
Overall, this thesis paves the way for developing a comprehensive foundation for utilizing DPT by-products by optimizing the parameters of surface modification, fibre geometry, fibre loading, and processing parameters for developing sustainable composites that can be industrialised for various non-structural industrial applications (i.e., construction and automotive industries)
- âŠ