A Review on Strengthening Steel Beams Using FRP under Fatigue

In recent decades, the application of fibre-reinforced polymer (FRP) composites for strengthening structural elements has become an efficient option to meet the increased cyclic loads or repair due to corrosion or fatigue cracking. Hence, the objective of this study is to explore the existing FRP reinforcing techniques to care for fatigue damaged structural steel elements. This study covers the surface treatment techniques, adhesive curing, and support conditions under cyclic loading including fatigue performance, crack propagation, and failure modes with finite element (FE) simulation of the steel bridge girders and structural elements. FRP strengthening composites delay initial cracking, reduce the crack growth rate, extend the fatigue life, and decrease the stiffness decay with residual deflection. Prestressed carbon fibre-reinforced polymer (CFRP) is the best strengthening option. End anchorage prevents debonding of the CRRP strips at the beam ends by reducing the local interfacial shear and peel stresses. Hybrid-joint, nanoadhesive, and carbon-flex can also be attractive for strengthening systems

Comparative Study Of Plant Biodiversity Data Modeling In Research Perspective

Despite the extensive research has been perform in plant biodiversity area recent years, managing plant biodiversity with database system still poses many challenges. Bio-diversity is the variety of different types of plants species that grows in various landscape. There is phenomenal growth in the area of biodiversity studies, largely motivated by its economic and humanitarian. Various data models, query languages and techniques have been proposed by many researchers. Data models for plant biodiversity have been developed to manage plant information, digital map data, and remotely sensed images. Plant biodiversity databases management systems can become an enabling technology for important applications like Plant biodiversity, Plant Taxonomy, Botanical Information System, Medicinal and Aromatic Plants. Most of the data models are based on relationql model. Relational model can not support temporal data (time), it only supports spatial data (space). Comparison has been made between existing plant biodiversity data model in computer perspective. Incorporation of the plant biodiversity and time can make an enhancement for the Plant biodiversity and analysis and manipulation. Integrate spatial and temporal information, it has becomes a critical issues in designing a data model. After the comparative study addressing the research issues in biodiversity databases but it will muse on the Plant Biodiversity Data Modeling is providing an analysis of challenges set, the problems come across as well as the proposed solutions and the phenomenal. Overviews the advance in plant biodiversity data model research

Spatio-Temporal object relational for biodiversity system (STORe-Biodi)

Spatio-temporal data model for biodiversity is 'owing importance to the biodiversity data anagement, forest and environment control. Datio-temporaldata models have received much tention in the database research community ~cause of their practical importance and teresting challenges they pose. This paper is scussed upon the research activities of 'lecting, designing, implementing the data odel. The paper can be divided by two major lrts, fIrst: discuss about biodiversity data model ld secondly: spatio-temporal conceptual amework design of biodiversity data model for ng terms stewardship of biodiversity formation. In this paper our main objective to inimize the extension required in SQL guage. This paper also focuses on the unifIed ode1s of space and time using object-relation ~proach.In particular, we propose a conceptual Dject-relational spatial temporal data model lsed on Donna J. Peuquet's pyramid framework. ndard and user management queries are ~pliedto test the model. After extensive testing, e data model performed admirably in anaging biodiversity data

Mitigation of plate end debonding in CFRP strengthened wide-flange steel I-beams under monotonic and fatigue loading / Mohamed Kamruzzaman

The use of the externally bonded reinforcement (EBR) technique with carbon fiber reinforced polymer (CFRP) is a recent and promising method for increasing the flexural capacity and fatigue life of steel structural elements. However, plate end-debonding is one of the main problems of CFRP strengthened steel beams. The CFRP end-debonding and end-delamination (EDL) causes premature failures for strengthened steel beams subjected to monotonic and cyclic loading, which is an essential issue that needs to be resolved. The aim of this study is to investigate the effectiveness of strengthening wide-flange steel I-beams using CFRP in order to increase the monotonic and fatigue flexural strength of the beams and improve against CFRP end debonding. This research highlights various approaches to improve the resistance against debonding by studying the CFRP in-plane end cutting shape, the combination of CFRP in-plane and tapering end shape, end anchorage, as well as the triangular spew fillet of adhesive at the tips of the CFRP plate. In addition, the effect of lateral bracing and stiffeners on the CFRP failure modes was also investigated. A total of twenty-five beams were fabricated and divided into two categories for the investigation, i.e. flexural monotonic and fatigue specimens. Furthermore, detailed finite element (FE) simulations have been conducted for the tested specimens. FE non-linear analyses has been carried out to simulate the flexural behavior of the beams under monotonic loading. The fatigue life was also predicted at constant load ranges for all tested steel beams using the FE simulations. The use of plate stiffeners and lateral bracing improve the overall performance of the strengthened beams. The application of the trapezoidal in-plane CFRP end cutting shape was found to be the best configuration for delaying the plate end debonding failure compared to the other end cutting shapes under both monotonic loadings and fatigue. Applying the combined trapezoidal in-plane and tapered CFRP end shape with triangular spew fillets of adhesive increased the load bearing capacity and delayed the plate debonding failure mode. Anchorage using CFRP fabrics at the end of CFRP plates mitigated the CFRP end problems, particularly end-debonding and EDL of strengthened beams. The FE simulation also showed that the trapezoidal is the best end cutting shape to delay plate debonding and the plate end anchorage using three layers with 220 x 175 mm CFRP fabrics is effective in mitigating end debonding initiation for monotonic and fatigue loading. The correlation between the results of the experiment and numerical modelling presented good agreements in this study

Biodiversity Data Model (BiDaM) Using Object Relational Approach: Conceptual Framework

The extensive research has been performed on plant biodiversity and even on mangrove area recent years; managing plant biodiversity data with database system still poses many challenges. Plant biodiversity is the variety of different types of plants species that growth in various landscape. There are phenomenal growths in the area of biodiversity studies, largely motivated by its economic and humanitarian. Various data models, query languages and techniques have been proposed by many researchers. Traditional database systems (built on relational hierarchical and network models) which are widely used for commercial applications such as banking fail to meet the modeling and processing requirements of the biodiversity data. Recently developed BODHI (Biodiversity Object Database arcHItecture) data model which is designed based on Indian plant biodiversity and only support spatial data. Integration between plant Bio-diversity data (BODHI) and geographical data with event-based approach can make an enhancement for the plant biodiversity data analysis and data manipulation. In addition, most of the data models are relational model. However, relational model can not support temporal data (time) effectively; it is best for spatial data (space). The main objective of the present study is to design a conceptual data model which will be later on complete data model for plant biodiversity. Conceptual data model is the extension of BODHI data model by using object relational data modeling and event-based approach to support temporal data. Therefore, conceptual data model by using object relational and event based is an appropriate approach to design a plant biodiversity data model. Moreover, Forest department, land and agricultural management and other related research organization could be benefited from the outcome of this model

Conceptual Spatio-Temporal Data Model Design For Plant Biodiversity

Malaysia has been acclaimed as one of the mega diversity countries in the world also has been ranked the 12th richest country in terms of the number and diversity of plant species. To manage the large amount of plant species of Malaysia has become very essential with rapid growth in the number of plant species due to their rich economic importance. Although the extensive research has been performed in plant biodiversity area recent years, managing plant biodiversity data with database system still poses many challenges. Traditional database systems (built on relational hierarchical and network models) which are widely used for commercial applications such as banking fail to meet the modeling and processing requirements of the biodiversity data. Recently developed BODHI (Biodiversity Object Database arcHItecture) data model which is designed based on Indian plant biodiversity and only support spatial data. Geographical data have an object and location, attribute and time. Integration between plant Biodiversity data (BODHI) and geographical data with event-based approach can make an enhancement for the plant biodiversity data analysis and data manipulation. In addition to this, most of the data models are relational model. However, relational model can not support temporal data (time) effectively; it is only support spatial data (space). Main purpose of this paper is to design a conceptual plant biodiversity data model which is combination of BODHI data model and event-based techniques by using object relational approach to support temporal data. Therefore, conceptual data model by using object relational and event based is an appropriate approach to design a plant biodiversity data model. Moreover, Forest department, land and agricultural management and other related research organization could be benefited from the outcome of this model

Object-relation data model (ORDM) for Malaysian biodiversity data.

The economic importance and uses of the large number of biodiversity plant species of Malaysia make it essential for their biodiversity to be conserved. The complexity of natural history collection information and similar information within the scope of biodiversity informatics poses significant challenges for effective management of plant biodiversity data. In order to undertake the steps for biodiversity 'conservation such as identification of species, monitoring climate conditions, it is essential to efficiently manage the vast amount of biodiversity related data. This paper discusses about the object-relational conceptual design of biodiversity data model for long term stewardship of biodiversity information. A plenty of data models have been developed (such as BODHI, Oshadhi) which only support spatial data. In addition to this, most of the data models are relational model. The purpose of this research is to design a biodiversity data model that better facilitates the exploration and analysis of spatio-temporal biodiversity data by using object relational data model techniques. The goal of this study is to design a biodiversity model that is efficient for data management and able to integrate diverse set of spatio-temporal data that maybe required for analysis, and monitoring biodiversity data

A novel dataset for baby broccoli identification by using YOLOv8 model

As global population increases, the need for agricultural automation becomes crucial for a stable food supply. An autonomous mechanism for picking baby broccoli could economically benefit farmers and society. To date, efforts to develop an automated baby broccoli harvesting solution have been absent. A key step in automation, particularly for the automated recognition of baby broccoli heads through computer vision, involves the creation of a rich dataset that sufficiently captures the characteristics of baby broccoli heads, as such a dataset has not yet been collected or published. This paper marks the first step towards automating baby broccoli harvesting by creating a novel dataset and testing its accuracy for precise identification. We have gathered data using custom software and a RealSense D435 Depth camera, known for its depth and stereo vision capabilities. The initial results of the model that was trained from our dataset had mAP values ranging from 0.869 to 0.942. This initial training shows that the dataset fits the purpose of detecting baby broccoli heads. Further results shows that when the model is 97.7% confident or more, its predictions are 100% precise. © 2024 IEEE

Work-in-progress paper : synergizing YOLOv8 and PCA for size estimation of baby broccoli

This research aims to advance agricultural automation by developing a machine learning-based method for accurately measuring harvest-ready baby broccoli through estimating the size of individual heads. Unlike traditional broccoli, baby broccoli's varying head depth complicates size estimation, making direct pixel-size conversion ineffective. To overcome this, we utilized depth-sensing cameras to capture precise dimensions. Our initial efforts involved curating a unique dataset and applying the YOLO computer vision algorithm for segmenting baby broccoli heads. We then calculated the size of each identified head using Principal Component Analysis (PCA). Given that baby broccoli tends to grow in tight clusters, our method includes tracking individual heads within a frame and associating them with specific size information to ensure accurate management of information. By incorporating stereo vision and depth data from the realsense D435 camera along with instance segmentation and PCA, our initial results achieved size estimates with an error rate below 10 %. The paper further recommends enhancing accuracy through a hybrid approach that combines deep learning, neural networks, and PCA. © 2024 IEEE

Measures of transport-related social exclusion: A critical review of the literature

Quantitative measures of transport disadvantage are reviewed in this paper from the perspective of their effectiveness to investigate social exclusion. The effectiveness is assessed using criteria derived through a review of the concepts of transport disadvantage and social exclusion and their operationalisation. The specified criteria are related to issues of spatial (e.g., urban accessibility, and public transport accessibility), temporal (e.g., public transport availability, and facility opening hours), and social attributes of travel and activity participation (e.g., personal mobility, and disability). Four groups of transport disadvantage measures are identified and evaluated. These include deprivation-based measures, mobility-based measures, accessibility-based measures, and activity-based measures. The review suggests that although the first three categories of measures have traditionally been used to identify transport disadvantage, they do not satisfy issues surrounding activity participation—the key outcome of social exclusion. The activity space concept is a way in which these issues can be incorporated, as it is a measure of the outcomes of activity participation and their associated travel to that activity. Participation in an activity means that an individual has overcome the spatial, temporal and social barriers of travel for that activity. The research using the activity space concept has, however, inadequately identified individual travel and activity participation. This has been due to a separate application of a range of different indicators to assess activity space size. These indicators are by their nature multidimensional—e.g., area visited, distance travelled, and number of activity sites visited. Although each indicator represents a specific qualitative/quantitative aspect of travel and activity participation, researchers have treated these indicators in an isolated manner to identify transport disadvantage and consequently transport-related social exclusion. This paper identifies the weaknesses and strengths associated with these measures; and methods are directed to overcome the limitations