Search results

Current research efforts exhibit a surge imperative for a building information modelling (BIM) approach that embodies a repository of all relevant data of existing building components while monitoring and consistently recording numerous components’ functions throughout its lifecycle, especially in Egypt. This research paper aims to develop an integrated as-is BIM-facility management (FM) information model for the existing building’s components via a case study, depicting a repository for historical data and knowledge amassed from inspections and conveying maintenance decisions automatically during the FM practices.

The developed approach pursues four successive steps: data acquisition and processing of building components; components recognition from point clouds; modelling scanned point clouds; and quick response code information transfer to BIM components.

The proposed approach incorporates the as-is BIM with the building components’ as-is FM information to portray a repository for historical data and knowledge collected from inspections to proactively benefit facility managers in simplifying, expediting and enhancing maintenance decisions automatically during FM practices.

This paper presents a digital alternative to manual maintenance recordkeeping concerning building components to retrieve their as-is and historical data using a case study in Egypt. This paper proposes a broad scan to as-is information BIM approach for the existing building’s components to condone maintenance interventions using a versatile, affordable, readily available and multi-functional method for scanning the building’s components using a handheld tool.

This study focused on exploring the performance factors (PFs) that impact Infrastructure Sanitation Projects (ISSPs) in the construction sector. The aim was twofold: firstly, to identify these crucial PFs and secondly, to develop a robust performance model capable of effectively measuring and assessing the intricate interdependencies and correlations within ISSPs. By achieving these objectives, the study aimed to provide valuable insights into and tools for enhancing the efficiency and effectiveness of sanitation projects in the construction industry.

To achieve the study's aim, the methodology for identifying the PFs for ISSPs involved several steps: extensive literature review, interviews with Egyptian industry experts, a questionnaire survey targeting industry practitioners and an analysis using the Relative Importance Index (RII), Pareto principle and analytic network process (ANP). The RII ranked factor importance,  and Pareto identified the top 20% for ANP, which determined connections and interdependencies among these factors.

The literature review identified 36 PFs, and an additional 13 were uncovered during interviews. The highest-ranked PF is PF5, while PF19 is the lowest-ranked. Pareto principle selected 11 PFs, representing the top 20% of factors. The ANP model produced an application for measuring ISSP effectiveness, validated through two case studies. Application results were 92.25% and 91.48%, compared to actual results of 95.77% and 97.37%, indicating its effectiveness and accuracy, respectively.

This study addresses a significant knowledge gap by identifying the critical PFs that influence ISSPs within the construction industry. Subsequently, it constructs a novel performance model, resulting in the development of a practical computer application aimed at measuring and evaluating the performance of these projects.

The study aims to verify and establish the result of the most suitable optimization approach for higher performance and lower emission of a variable compression ratio (VCR) diesel engine. In this study, three types of test fuels are taken and tested in a variable compression ratio diesel engine (compression ignition). The fuels used are conventional diesel fuel, e-diesel (85% diesel-15% bioethanol) and nano-fuel (85% diesel-15% bioethanol-25 ppm Al₂O₃). The effect of bioethanol and nano-particles on performance, emission and cost-effectiveness is investigated at different load and compression ratios (CRs). The optimum performance and lower emission of the engine are evaluated and compared with other optimization methods.

The test engine is run by diesel, e-diesel (85% diesel-15% bioethanol) and nano-fuel (85% diesel-15% bioethanol-25 ppm Al₂O₃) in three different loadings (4 kg, 8 kg and 12 kg) and CR of 14, 16 and 18, respectively. The optimum value of energy efficiency, exergy efficiency, NO_X emission and relative cost variation are determined against the input parameters using Taguchi-Grey method and confirmed by response surface methodology (RSM) technique.

Using Taguchi-Grey method, the maximum energy and exergy efficiency, minimum % relative cost variation and NO_X emission are 24.64%, 59.52%, 0 and 184 ppm, respectively, at 4 kg load, 18 CR and fuel type of nano-fuel. Using RSM technique, maximum energy and exergy efficiency are 24.8% and 62.9%, and minimum NO_X emission and % cost variation are 208.4 ppm and –6.5, respectively, at 5.2 kg load, 18 CR and nano-fuel. The RSM is suggested as the most appropriate technique for obtaining maximum energy and exergy efficiency, and minimum % relative cost; however, for lowest possible NO_X emission, the Taguchi-Grey method is the most appropriate.

Waste rice straw is used to produce bioethanol. 4-E analysis, i.e. energy, exergy, emission and economic analysis, has been carried out, optimized and compared.

Academics and businesses alike have begun to recognise sustainability as a vital component of supply chain competitive advantage in recent years. Inconclusive results have been found in empirical studies of sustainable supply chain management (SSCM) that have ignored contextual variables concerning the dynamic role of firm capability in favour of testing alternative assumptions about the effect of various elements of the triple bottom line (TBL) on firm performance outcomes. The present study examines whether and how firm capabilities mediate the connection between SSCM, from a TBL standpoint, and firm financial performance outcomes.

Using the stakeholder theory, the study employed 325 survey responses from firms operating in different industries in Ghana (a less-researched context but one that plays a key role regarding SSCM practices) and the partial least squares structural equation model (PLS-SEM) technique to simultaneously assess the relationships amongst the variables.

It was discovered that the connections between all the TBL facets of SSCM practices and firm performance are positive and significant, and these relationships are mediated by firm capabilities.

By examining the underlying variables and relationships that contribute to the establishment of the rather complex relationship between SSCM practices from a TBL perspective and the performance of a firm, the research contributes to current knowledge on SSCM practices, firm capabilities and firm performance.

This paper aims to achieve accurate maximum power from solar photovoltaic (PV), its five parameters need to be estimated. This study proposes a novel optimization technique for parameter estimation of solar PV.

To extract optimal parameters of solar PV new optimization technique based on the Jellyfish search optimizer (JSO). The objective function is defined based on two unknown variables and the proposed technique is used to estimate the two unknown variables and the rest three unknown variables are estimated analytically.

In this paper, JSO is used to estimate the parameters of a single diode PV model. In this study, eight different PV panels are considered. In addition, various performance indices, such as PV characteristics, such as power-voltage and current-voltage curves, relative error (RE), root mean square error (RMSE), mean absolute error (MAE) and normalized mean absolute error (NMAE) are determined using the proposed algorithm and existing algorithms. The results for different solar panels have been obtained under varying environmental conditions such as changing temperature and constant irradiance or changing irradiance and constant temperature.

The proposed technique is new and provides better results with minimum RE, RMSE, NMAE, MAE and converges fast, as depicted by the fitness graph presented in this paper.

This research aims to study the materials that compose older reinforced concrete bridges which are damaged and degrading to explain the mechanisms and origins of various disorders. Therefore, this work will contribute to providing answers on the capacity of nondestructive evaluation method during the diagnosis. In addition to the characterization of affected structures, it will aim to provide effective solutions for different serious pathologies.

In this context, two bridges located on NH16 and NH21, respectively, were studied in Annaba city (north-east Algeria), specifically in El-Hadjar municipality located in the central industrial zone of Pont-Bouchet. This study makes it possible to make conclusions from the in-depth diagnosis based on disorders exposition causes and mechanical characteristics evolution by non-destructive testing (NDT) tools. Furthermore, solutions are proposed, including conservation maintenance of these degraded structures.

All degradations can be the result of several factors: either human (poor design) or chemical (surface water, wastewater and groundwater quality (acidic or basic)). In addition to other natural causes (geological formations, flood phenomena or climate), NDT tools play a major role in the evaluating mechanical performance of degraded structures (resistance and hardness).

The NDT techniques can be transmitted to civil engineering experts because their training is limited regarding mechanical and structural construction.

NDT tools are the most suitable for in-situ assessing, and the concrete constructions health state, so far from financial problems.

Degraded bridge diagnosis by NDT testing is necessary for a thorough safety evaluation (mechanical performance, strength and deformability), to protect human lives and design durability.

This is an original paper which contains new information at different scales and from special fields, based on an evaluation using NDT tools on real degraded structures. It can be used to improve the knowledge of materials employed in a bridge without performing expensive direct tests or the need for destroying it.