97 research outputs found
Fatigue studies on impacted and unimpacted CFRP laminates
No full textCarbon fiber-reinforced polymer (CFRP) composites are widely used in safety-critical aerospace structures and experience low-velocity impacts, which deteriorate their residual strength and residual life. This paper presents the results of damage accumulation during fatigue loading, estimated through stiffness degradation under constant amplitude and the programmed version of FALSTAFF spectrum loading (Prog-FALSTAFF) of [0/90]8 and quasi-isotropic CFRP laminates. The laminates are prepared by a hand lay-up technique; specimens of size 250 mm by 45 mm by 4.5 mm thickness are extracted from the laminate for testing. Some of the specimens are subjected to drop impact at different input impact energies (23J, 35J, and 51J), and the fatigue response after impact loading is studied. The rate of degradation of stiffness for impacted CFRP specimens under a Prog-FALSTAFF spectrum loading is less compared to constant amplitude loading. The sequence of intermediate block cycles of constant ampltiude in Prog-FALSTAFF is organized either in an ascending order of magnitude, low to high (Lo-Hi), or in a descending order of magnitude (Hi-Lo) to study the effect of load sequencing on damage accumulation. Lo-Hi sequencing results in greater damage compared to Hi-Lo sequencing for all the orientations of CFRP laminates studied. In the case of unimpacted specimens, there is a marginal increase in stiffness in the early stages, followed by a drop in stiffness; the stiffness degradation rate in unimpacted specimens is much less compared to impacted specimens. Computed X-ray tomography has been carried out on specimens under the following conditions: pristine; after fatigue cycling; after impact damage; and postimpact, postfatigue cycling to understand the damage progression. As an exploratory study, investigation of damage through active infrared thermography is carried out. The presence of delamination could be identified through the variable specimen cooling curves of CFRP specimens using the active thermography technique
Automated decision-making for the end-of-life scenario of steel structures using convolutional neural networks
No full textLAUREA MAGISTRALEIl settore edile è il principale contributore alle emissioni globali di gas serra (GHG), al consumo di risorse e alla produzione di rifiuti legati alla demolizione. Una riduzione di questi impatti ambientali può essere ottenuta recuperando i rifiuti edili attraverso la decostruzione selettiva e il riutilizzo dei materiali. Sfortunatamente, il riciclaggio è la pratica più comune nella gerarchia della gestione dei rifiuti e non è efficiente in termini di energia e materiali come il riutilizzo. Pertanto, il riutilizzo dovrebbe essere promosso per una migliore gestione dei rifiuti e un uso efficiente dei materiali. L'ambiente costruito può trarre vantaggio dall'economia circolare e dai principi della digitalizzazione per promuovere pratiche di riutilizzo. Tuttavia, l'assenza di un quadro decisionale consolidato per identificare gli elementi strutturali riutilizzabili e la mancanza di iniziative per l'adozione di tecnologie avanzate per il riutilizzo rallentano l'attuazione pratica nell'ambiente edificato.
In questa tesi, viene sviluppato un framework decisionale multi-criterio con uno strumento di rete neurale convoluzionale automatizzato che riconosce la corrosione, i tipi di connessione e i danni associati dalle immagini della struttura in acciaio, con una precisione complessiva dell' 83%, 89% e 83%, rispettivamente. Per convalidare lo strumento e dimostrare il potenziale della ricerca, il quadro decisionale viene applicato a un caso di studio della costruzione di strutture in acciaio da un progetto di riutilizzo del mondo reale. Il quadro si riferisce alla fattibilità delle decisioni sul riutilizzo di elementi strutturali da edifici fuori uso e, a seconda della percentuale di riutilizzo, indica che è possibile risparmiare fino a 106.000 kgCO2e dalla pratica di riutilizzo per il caso di studio considerato.
Questo quadro ha lo scopo di fornire un forte sistema di supporto alle parti interessate e ai decisori nell'ambiente costruito. Di conseguenza, riduce il rischio e le incertezze associate al riutilizzo degli elementi strutturali del parco edilizio fuori uso. Infine, un processo decisionale efficiente può contribuire positivamente all'obiettivo di ridurre le emissioni di gas a effetto serra causate dal settore dell'architettura, dell'ingegneria e delle costruzioni (AEC). Il metodo sviluppato in questa tesi può essere esteso anche ad altre tipologie edilizie per facilitare ulteriormente il riutilizzo di componenti e materiali ampiamente utilizzati nell'industria.The construction industry is the main contributor to global greenhouse gas (GHG) emissions, resource consumption and demolition-related waste generation. A reduction in these environmental impacts can be achieved by recovering building waste through selective deconstruction and material reuse. Unfortunately, recycling is the most common practice in the waste management hierarchy, and it is not as energy- and material-efficient as reuse. Therefore, reuse should be promoted for better waste management and efficient use of materials. The built environment can take advantage of circular economy and digitalization principles to promote reuse practices. However, the absence of an established decision-making framework to identify reusable structural elements and the lack of initiatives to adopt advanced technologies for reuse slow down the practical implementation in the built environment.
In this thesis, a multi-criteria decision-making framework is developed with an automated convolutional neural network tool that recognizes corrosion, connection types and associated damage from steel structure images, with an overall accuracy of 83%, 89%, and 83%, respectively. To validate the tool and demonstrate the potential of the research, the decision-making framework is applied to a case study of steel frame building from a real-world reuse project. The framework refers to the feasibility of decisions around reusing structural elements from end-of-life buildings, and depending on the reuse percentage, it indicated that up to 106,000 kgCO2e can be saved from reuse practice for the considered case study.
This framework is intended to provide a strong supportive system to the stakeholders and decision-makers in the built environment. As a result, it reduces the risk and uncertainties associated with reusing structural elements from end-of-life building stock. Finally, efficient decision-making can positively contribute to the goal of reducing GHG emissions caused by the Architecture, Engineering, and Construction (AEC) industry. The method developed in this thesis can also be extended to other building types to further facilitate the reuse of components and materials widely used in the industry
Do Labor Intensive Industries Generate Employment? Evidence from firm level survey in India
Get PDFThis study attempts to address the issue of declining labour intensity in Indias organized manufacturing in order to understand the constraints on employment generation in the labour intensive sectors. Using primary survey data covering 252 labour intensive manufacturing-exporting firms across five sectorsapparel, leather, gems and jewellery, sports goods, and bicycles for 2005-06 an attempt is made to find out the factors which constrain employment generation in labour intensive firms. The study shows several constraints in the path of employment generation in labour intensive sectorsnon-availability of trained skilled workers, infrastructure bottlenecks, low levels of investment, labour rules and regulations, and a noncompetitive export orientation. The study suggests a set of policy initiatives to improve the employment potential of these sectors.Indian Organized Manufacturing, Labor Intensity, Employment Growth, Skilled workforce, Wage Structure, Export status, Machinery Usage, Labor laws, South Asia
Data requirements and availabilities for material passports: A digitally enabled framework for improving the circularity of existing buildings
No full textPassports for circularity, e.g., digital product passports and material passports (MPs), have gained recognition as essential policy instruments for the Circular Economy goals of the European Union. Despite the growing number of approaches, there is a lack of knowledge about the data requirements and availabilities to create MPs for existing buildings. By deploying a mixed-method research design, this study identified the potential users and their data needs within the context of European social housing organisations. Three rounds of validation interviews with a total of 38 participants were conducted to create a data template for an MP covering maintenance, renovation, and demolition stages. This data template was then tested in a case study from the Netherlands to determine critical data gaps in creating MPs, including, but not limited to the composition of materials, presence of toxic or hazardous contents, condition assessment, and reuse and recycling potential of a product. Finally, an MP framework is proposed to address these data gaps by utilising the capabilities of enabling digital technologies (e.g., artificial intelligence and scanning systems) and supportive knowledge of human actors. This framework supports further research and innovation in data provision in creating MPs to narrow, slow, close, and regenerate the loops.Real Estate ManagementDesign & Construction Managemen
Post-Impact Thermo-Mechanical Response of Woven Mat Composites Subjected to Tensile Loading
No full textThe thermo-mechanical response of carbon fiber reinforced polymer (CFRP) laminates subjected to continuous tensile loading and programmed interrupted tensile loading is examined to understand the changes due to damage progression. Quasi-isotropic laminates were prepared using 500 GSM twill weave carbon fabric with LY 556 resin and HY 991 hardener by hand lay-up technique, followed by curing under hot compression. A few specimens were subjected to an impact loading to 23 J and 51 J energy levels using a hemispherical tip to induce low velocity impact damage. Passive thermal imaging of woven CFRP laminates during tensile testing was captured using a TIM 160 Micro-epsilon infrared thermal camera. Temperature response during tensile testing provided a good correlation with deformation mode esp. for specimens impacted with 51 J of energy.
Tensile tests were interrupted at periodic loads and unloaded and reloaded to study the thermal response after prior plastic deformation damage in the specimen. Unlike the case of GFRP specimens, distinct changes in thermo-elastic slope due to prior plastic deformation damage could not be clearly identified. As impact damage resulted in de-lamination of some layers, active thermography technique was used to study the rate of cooling of specimen with time when the damage is closer to the camera face as well as when it is away from the camera face. The cooling curves obtained were found to be dependent on the location of the damage, as well as on heating face of the specimen.</jats:p
Low frequency dielectric dispersion study of PVC-PPy blends in dilute solution of different solvents
No full textStudy of temperature dependent electrical properties of Se80-xTe20Bix (x = 0, 3, 6) glasses
No full textASSESSMENT OF THE EFFECTS OF WHOLE BODY AND REGIONAL SOFT TISSUE COMPOSITION ON BONE STRENGTH AND DEVELOPMENT IN FEMALES.
No full textRights Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author
The impact of grocery store podcasts in the delivery of nutrition education to improve shopping behaviors, particularly the purchase of omega-3 rich foods
No full textOmega-3 (n-3) fatty acids are important nutrients and are deficient in the American diet. Therefore increasing the intake of n-3s is a public health goal. Research has suggested that because people eat what they buy, point-of-purchase interventions may have the potential to help consumers make healthy food choices. A study of existing literature revealed that these interventions have not used newer technological means, have many limitations, and have failed to assess long-term shopping behavior change. The research presented in this dissertation aims to test use of, and long-term effects of, new technology (i.e., podcasts) as a means of delivering nutrition education at the grocery store to interested consumers while they shop. A single-group, repeated-measures, mixed-methods study design was employed to determine if listening to a podcast about n-3s while grocery shopping increased shoppers’ awareness about, and purchases of, seafood and other foods rich in n-3s. Constructs from the Theory of Reasoned Action were used to evaluate the effectiveness of the podcasts. A secondary data analysis of participant food purchase data was done to examine the long-term effects of podcast exposure over the six months following the intervention (as compared to the six months prior). As a result of exposure to the podcasts TRA constructs improved, knowledge about n-3s increased and misconceptions were reduced. In addition, both long-term (six months post-intervention) and short-term purchases (day of the intervention) of n-3 rich food item purchases increased. These findings suggest that podcasts may be an effective means to communicate nutrition education messages at the point of purchase, to those who indicate an interest in the subject.Ph. D.Includes bibliographical referencesby Deepika Bangi
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