This page has only limited features, please log in for full access.

Prof. Dr. Emad Elbeltagi
Structural Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt

Basic Info


Research Keywords & Expertise

0 Multi-criteria Decision Analysis
0 Optimization
0 Sustainability
0 Civil infrastructure and asset management
0 Artificial intelligence applications in construction

Fingerprints

Optimization

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 01 July 2021 in Journal of Construction Engineering and Management
Reads 0
Downloads 0

Game theory provides a rigorous mathematical approach to evaluate and predict stakeholders’ interactions. Even though the construction industry is rich with encounters among its stakeholders, construction engineering and management (CEM) research lacks a thorough investigation of game-theoretic applications. This paper presents an overview of the current game-theoretic models in CEM research, aiming to enhance the understanding of the applications of game theory in analyzing CEM strategic interactions within multiple application domains and project delivery systems (PDSs). The authors analyzed 87 CEM peer-reviewed publications employing game-theoretic models between 1998 and 2019. The analysis accounted for CEM application domain, involvement of stakeholders, PDS addressed, and type of game theoretic solution used in each publication. The authors performed a Social Network Analysis (SNA) of the current game-theoretic interactions, identifying literature trends and gaps to be addressed in future research. Unlike traditional literature review methods, SNA provides a quantitative approach in analyzing the existing body of knowledge. Research findings demonstrate the contributions of game theory in seven CEM applications (conflict resolution; bargaining and negotiations; allocation of cooperative benefits; governance and supervision; evolution of cooperation and trust; construction bidding; and risk allocation). Through SNA, the highest degree centrality levels were found in Owner-Contractor games in the context of CEM bidding, conflict resolution, as well as bargaining and negotiations. SNA also revealed the need for further investigation of interactions among CEM stakeholders within PDS other than the traditional Design-Bid-Build and Public-Private-Partnerships. Moreover, games featuring strategic alliances and supply chains of multiagents can provide more adequate reflections of actual interactions.

ACS Style

Radwa Eissa; Mohamed S. Eid; Emad Elbeltagi. Current Applications of Game Theory in Construction Engineering and Management Research: A Social Network Analysis Approach. Journal of Construction Engineering and Management 2021, 147, 04021066 .

AMA Style

Radwa Eissa, Mohamed S. Eid, Emad Elbeltagi. Current Applications of Game Theory in Construction Engineering and Management Research: A Social Network Analysis Approach. Journal of Construction Engineering and Management. 2021; 147 (7):04021066.

Chicago/Turabian Style

Radwa Eissa; Mohamed S. Eid; Emad Elbeltagi. 2021. "Current Applications of Game Theory in Construction Engineering and Management Research: A Social Network Analysis Approach." Journal of Construction Engineering and Management 147, no. 7: 04021066.

Journal article
Published: 04 May 2021 in Energy Reports
Reads 0
Downloads 0

Controlling buildings energy consumption is a great practical significance. During early design stage, accurate and rapid prediction of energy consumption could provide a quantitative basis for energy-saving designs. Currently, the key problem that are still facing designers is the interoperability between building modeling and energy simulation tools. In addition, design challenges gained recognition due to the complexity of the prevalence of large numbers of independent interrelated variables. Artificial Neural Networks (ANNs) are the most broadly applied artificial intelligence method in buildings’ performance field due to its competence to handle nonlinear variables’ relationships accurately and promptly. This paper presents a methodology based on the ANNs to improve the prediction of energy usage for residential buildings in early design stages. The model is created using a dataset resulted from the calculation of energy consumption by simulating multiple design options with randomly input variables. The proposed methodology can mitigate technical barriers while integrating and automating available commercial tools into a workflow from a parametric model to the simulation of building energy. The developed ANN model is evaluated and validated and used to predict the energy consumption with acceptable accuracy. Finally, a user-friendly interface is designed to facilitate energy consumption prediction without any experience in modeling and simulation tools acting as a decision support tool, which is simple, reliable and easy to use.

ACS Style

Emad Elbeltagi; Hossam Wefki. Predicting energy consumption for residential buildings using ANN through parametric modeling. Energy Reports 2021, 7, 2534 -2545.

AMA Style

Emad Elbeltagi, Hossam Wefki. Predicting energy consumption for residential buildings using ANN through parametric modeling. Energy Reports. 2021; 7 ():2534-2545.

Chicago/Turabian Style

Emad Elbeltagi; Hossam Wefki. 2021. "Predicting energy consumption for residential buildings using ANN through parametric modeling." Energy Reports 7, no. : 2534-2545.

Journal article
Published: 01 May 2021 in Journal of Management in Engineering
Reads 0
Downloads 0

Construction joint ventures (CJVs) execute business by pooling diverse technical and financial contributions from collaborating entities. Traditional CJV profit-allocation approaches account only for investment shares, and do not address the marginal contribution of the participating parties. Therefore, disagreements may arise between stakeholders. This research aims to reduce profit-share-related disagreements among multiple CJV members by allocating profit based on the marginal contribution of each party. The authors developed a conceptual framework using the Shapley value as an alternative to the traditional investment-based approach. Three illustrative examples demonstrated the possible use of the developed conceptual framework. Results of the study highlighted the potential of Shapley value as an alternative profit allocation scheme. The stability of the generated results was validated mathematically, and decision makers’ perception of fairness was addressed following the methods of prior experimental cooperative game theory research. This paper contributes to the body of knowledge by proposing an axiomatically fair methodology for profit-sharing negotiations among multiple collaborating parties in a project. This approach can be utilized in other engineering domains where the management needs to foster stable and fair collaborations among its stakeholders.

ACS Style

Radwa Eissa; Mohamed S. Eid; Emad Elbeltagi. Conceptual Profit Allocation Framework for Construction Joint Ventures: Shapley Value Approach. Journal of Management in Engineering 2021, 37, 04021016 .

AMA Style

Radwa Eissa, Mohamed S. Eid, Emad Elbeltagi. Conceptual Profit Allocation Framework for Construction Joint Ventures: Shapley Value Approach. Journal of Management in Engineering. 2021; 37 (3):04021016.

Chicago/Turabian Style

Radwa Eissa; Mohamed S. Eid; Emad Elbeltagi. 2021. "Conceptual Profit Allocation Framework for Construction Joint Ventures: Shapley Value Approach." Journal of Management in Engineering 37, no. 3: 04021016.

Original contribution
Published: 07 November 2020 in Journal of The Institution of Engineers (India): Series A
Reads 0
Downloads 0

The time–cost trade-off has been recognized as a very significant aspect of construction management. Generally, time–cost trade-off can be modeled as a fuzzy linear programming problem with symmetric or non-symmetric fuzzy numbers. However, it was successfully solved when the fuzzy membership functions are only symmetric. In the present work, a novel approach is introduced to solve fuzzy linear programming problem with non-symmetric fuzzy membership functions by transforming it to its corresponding nearest symmetric one. The transformed problem is then converted to its crisp linear programming problem and then solved by the standard primal simplex method. Two examples are presented to show the effectiveness of the proposed approach, and the results are discussed.

ACS Style

Israa Elkalla; Emad Elbeltagi; Mohamed El Shikh. Solving Fuzzy Time–Cost Trade-Off in Construction Projects Using Linear Programming. Journal of The Institution of Engineers (India): Series A 2020, 102, 267 -278.

AMA Style

Israa Elkalla, Emad Elbeltagi, Mohamed El Shikh. Solving Fuzzy Time–Cost Trade-Off in Construction Projects Using Linear Programming. Journal of The Institution of Engineers (India): Series A. 2020; 102 (1):267-278.

Chicago/Turabian Style

Israa Elkalla; Emad Elbeltagi; Mohamed El Shikh. 2020. "Solving Fuzzy Time–Cost Trade-Off in Construction Projects Using Linear Programming." Journal of The Institution of Engineers (India): Series A 102, no. 1: 267-278.

Journal article
Published: 31 October 2020 in Ain Shams Engineering Journal
Reads 0
Downloads 0

This paper presents a methodology to find the optimal design or rehabilitation of water distribution system (WDS) under both steady-state and transient conditions. Then, assessing the obtained optimal solution and studying its stability, reliability, due to uncertainty in pipe roughness coefficients (CHW). The WDS optimization objective is to minimize the rehabilitation cost by installing new pipes parallel to the existing ones achieving all hydraulic constraints. For this purpose, particle swarm optimization (PSO) is used as an optimization tool and Monte Carlo simulation (MCS) is applied to generate multiple realizations of CHW for different coefficient of variation (COVCHW). A comparison between crisp shape and continuous shape (S-shape) fuzzy membership functions is carried out to study the hydraulic availability indices to nodal pressure head values resulted from pipe roughness uncertainty. Both steady-state nodal and system reliabilities are estimated while, only the transient system reliability is calculated for the obtained optimal solution. The proposed methodology is applied on the New York City tunnel network (NYCTN) and the corresponding reliability is analyzed. Results show that as pipe roughness uncertainty increases, WDS reliability decreases.

ACS Style

Hamdy A. El-Ghandour; Samer M. Elabd; Emad Elbeltagi. Assessment of optimal water distribution systems design under steady-state and transient conditions due to pipe roughness uncertainty. Ain Shams Engineering Journal 2020, 12, 465 -473.

AMA Style

Hamdy A. El-Ghandour, Samer M. Elabd, Emad Elbeltagi. Assessment of optimal water distribution systems design under steady-state and transient conditions due to pipe roughness uncertainty. Ain Shams Engineering Journal. 2020; 12 (1):465-473.

Chicago/Turabian Style

Hamdy A. El-Ghandour; Samer M. Elabd; Emad Elbeltagi. 2020. "Assessment of optimal water distribution systems design under steady-state and transient conditions due to pipe roughness uncertainty." Ain Shams Engineering Journal 12, no. 1: 465-473.

Journal article
Published: 19 June 2020 in Applied Sciences
Reads 0
Downloads 0

Structural health monitoring (SHM) techniques are used to assess the behavior of structures during or after construction. The high cost of sensors is the main reason for the limited use of the SHM techniques. The present study investigates the dynamic behavior (dynamic acceleration, semi-static displacement, frequency and damping ratio) of highway steel plate girder bridges using strain measurements. The double filtration and polynomial prediction methods are used to estimate the dynamic behavior of the bridge using real-time strain measurements. To verify the accuracy of the developed method, the field monitoring measurements of the WonHyo bridge is used. The bridge behavior under different truck speeds and weights is observed and evaluated. The displacement and acceleration measurements are used to examine the results of the proposed method. The results of this study demonstrate that the strain measurements can be used to obtain an accurate semi-static displacement and dominant frequency content of the bridge. The accuracy of the developed model for the semi-static and dynamic behaviors is 99% and 69%, respectively.

ACS Style

Mosbeh R. Kaloop; Emad Elbeltagi; Jong Wan Hu. Estimating the Dynamic Behavior of Highway Steel Plate Girder Bridges Using Real-Time Strain Measurements. Applied Sciences 2020, 10, 4215 .

AMA Style

Mosbeh R. Kaloop, Emad Elbeltagi, Jong Wan Hu. Estimating the Dynamic Behavior of Highway Steel Plate Girder Bridges Using Real-Time Strain Measurements. Applied Sciences. 2020; 10 (12):4215.

Chicago/Turabian Style

Mosbeh R. Kaloop; Emad Elbeltagi; Jong Wan Hu. 2020. "Estimating the Dynamic Behavior of Highway Steel Plate Girder Bridges Using Real-Time Strain Measurements." Applied Sciences 10, no. 12: 4215.

Technical paper
Published: 25 May 2020 in Innovative Infrastructure Solutions
Reads 0
Downloads 0

Pavement evaluation is conducted to assess the functional and/or structural condition of existing pavement systems which can be done on project or network levels. Through pavement condition assessment, pavement deterioration models can be established and thus maintenance and rehabilitation alternatives can be proposed. The prediction of pavement performance which is primarily based on the pavement evaluation results is a critical element of a successful pavement management system (PMS). The main objective of this research is to revise and modify the current pavement condition rating (PCR) method for pavement evaluation as a major component of an effective PMS for roads and transport directorates in Egypt. Pavement condition data were collected from literature, General authority of roads, bridges and land transport in Egypt and the long-term pavement performance (LTPP) database. Due to its accuracy, only the LTPP data were used to modify the current PCR method to yield comparable values to the very well-known pavement condition index (PCI). The proposed modified PCR was validated using pavement distress data collected from two rural roads in Egypt, and the data showed reasonable accuracy as compared to the PCI method.

ACS Style

E. M. Ibrahim; S. M. El-Badawy; M. H. Ibrahim; Emad Elbeltagi. A modified pavement condition rating index for flexible pavement evaluation in Egypt. Innovative Infrastructure Solutions 2020, 5, 1 -17.

AMA Style

E. M. Ibrahim, S. M. El-Badawy, M. H. Ibrahim, Emad Elbeltagi. A modified pavement condition rating index for flexible pavement evaluation in Egypt. Innovative Infrastructure Solutions. 2020; 5 (2):1-17.

Chicago/Turabian Style

E. M. Ibrahim; S. M. El-Badawy; M. H. Ibrahim; Emad Elbeltagi. 2020. "A modified pavement condition rating index for flexible pavement evaluation in Egypt." Innovative Infrastructure Solutions 5, no. 2: 1-17.

Journal article
Published: 27 March 2020 in ISPRS International Journal of Geo-Information
Reads 0
Downloads 0

Monitoring the dynamic behavior of shorelines is an essential factor for integrated coastal management (ICM). In this study, satellite-derived shorelines and corresponding eroded and accreted areas of coastal zones have been calculated and assessed for 15 km along the coasts of Ezbet Elborg, Nile Delta, Egypt. A developed approach is designed based on Landsat satellite images combined with GIS to estimate an accurate shoreline changes and study the effect of seawalls on it. Landsat images for the period from 1985 to 2018 are rectified and classified using Supported Vector Machines (SVMs) and then processed using ArcGIS to estimate the effectiveness of the seawall that was constructed in year 2000. Accuracy assessment results show that the SVMs improve images accuracy up to 92.62% and the detected shoreline by the proposed method is highly correlated (0.87) with RTK-GPS measurements. In addition, the shoreline change analysis presents that a dramatic erosion of 2.1 km2 east of Ezbet Elborg seawall has occurred. Also, the total accretion areas are equal to 4.40 km2 and 10.50 km2 in between 1985-and-2000 and 2000-and-2018, respectively, along the southeast side of the study area.

ACS Style

Mohamed T. Elnabwy; Emad Elbeltagi; Mahmoud M. El Banna; Mohamed M.Y. Elshikh; Ibrahim Motawa; Mosbeh R. Kaloop. An Approach Based on Landsat Images for Shoreline Monitoring to Support Integrated Coastal Management—A Case Study, Ezbet Elborg, Nile Delta, Egypt. ISPRS International Journal of Geo-Information 2020, 9, 199 .

AMA Style

Mohamed T. Elnabwy, Emad Elbeltagi, Mahmoud M. El Banna, Mohamed M.Y. Elshikh, Ibrahim Motawa, Mosbeh R. Kaloop. An Approach Based on Landsat Images for Shoreline Monitoring to Support Integrated Coastal Management—A Case Study, Ezbet Elborg, Nile Delta, Egypt. ISPRS International Journal of Geo-Information. 2020; 9 (4):199.

Chicago/Turabian Style

Mohamed T. Elnabwy; Emad Elbeltagi; Mahmoud M. El Banna; Mohamed M.Y. Elshikh; Ibrahim Motawa; Mosbeh R. Kaloop. 2020. "An Approach Based on Landsat Images for Shoreline Monitoring to Support Integrated Coastal Management—A Case Study, Ezbet Elborg, Nile Delta, Egypt." ISPRS International Journal of Geo-Information 9, no. 4: 199.

Articles
Published: 07 July 2019 in International Journal of Pavement Engineering
Reads 0
Downloads 0

International Roughness Index (IRI) and Pavement Condition Index (PCI) are among other pavement condition indices used to assess pavement surface condition. The literature suggests that most of the pavement indices are related as a result of which several models have been developed to predict one index from the other. This study uses the Long-Term Pavement Performance (LTPP) database to develop a simplified regression model that links PCI with IRI. Measured pavement distresses from 1448 LTPP sections from the Specific Pavement Studies (SPS) and General Pavement Studies (GPS) representing 12744 data points were utilised for the PCI estimation. A total of 1208 sections with 10868 data points were used for model development while 240 sections with 1876 data points were used for the model validation. A sigmoid function is found to best express the relationship between PCI and IRI with a coefficient of determination (R2) of 0.995. The bias in the predicted IRI values is significantly very low. The model validation using a different dataset also yielded highly accurate predictions (R2 = 0.992). Finally, a pavement condition rating based on IRI is proposed. This system yields rating equivalent to the widely used PCI rating method which is based on the pavement condition.

ACS Style

Amr A. Elhadidy; Sherif M. El-Badawy; Emad Elbeltagi. A simplified pavement condition index regression model for pavement evaluation. International Journal of Pavement Engineering 2019, 22, 643 -652.

AMA Style

Amr A. Elhadidy, Sherif M. El-Badawy, Emad Elbeltagi. A simplified pavement condition index regression model for pavement evaluation. International Journal of Pavement Engineering. 2019; 22 (5):643-652.

Chicago/Turabian Style

Amr A. Elhadidy; Sherif M. El-Badawy; Emad Elbeltagi. 2019. "A simplified pavement condition index regression model for pavement evaluation." International Journal of Pavement Engineering 22, no. 5: 643-652.

Conference paper
Published: 13 June 2019 in Computing in Civil Engineering 2019
Reads 0
Downloads 0

Scheduling linear projects requires an optimization tool that does not only minimizes project duration and cost, but also maximizes the utilization of crews, accounts for travelling distance between units, and meets the delivery dates of the project’s units. This paper presents a multi-objective optimization model for scheduling linear projects through developing set of non-dominated optimal schedules. The proposed model consists of: (1) a resource driven scheduling module accounting for heterogeneity among construction crews, and (2) an evolutionary optimization module via genetics algorithms (GAs) and Pareto front sorting (PFS) that searches the solution space for optimal schedules. The model is tested on a case study drawn from the literature and provided significantly better results compared to some of the well-recognized scheduling models. The proposed model is coded using Visual Basics for Applications on a commercial scheduling tool and can be easily adopted by practitioners to provide a broad-spectrum of optimal schedules.

ACS Style

Mohamed S. Eid; Emad E. Elbeltagi; Islam H. El-Adaway. Multi-Objective Simultaneous Optimization for Linear Projects Scheduling. Computing in Civil Engineering 2019 2019, 1 .

AMA Style

Mohamed S. Eid, Emad E. Elbeltagi, Islam H. El-Adaway. Multi-Objective Simultaneous Optimization for Linear Projects Scheduling. Computing in Civil Engineering 2019. 2019; ():1.

Chicago/Turabian Style

Mohamed S. Eid; Emad E. Elbeltagi; Islam H. El-Adaway. 2019. "Multi-Objective Simultaneous Optimization for Linear Projects Scheduling." Computing in Civil Engineering 2019 , no. : 1.

Conference paper
Published: 13 June 2019 in Computing in Civil Engineering 2019
Reads 0
Downloads 0

Planning an efficient construction site layout increases safety and productivity of operations. As opposed to considering only confined construction sites, this paper optimizes site layout for linear infrastructure projects in congested inner cities roads (i.e., road maintenance). The construction site location of these projects dynamically changes as the work progresses. Therefore, selecting construction facilities locations (CFL) is a major problem prior to organizing these facilities. The presented work optimizes CFL selection in inner-cities congested roads, using uniform-cost search (UCS) as an optimization tool, through minimizing the (1) resources transportation cost, (2) land renting cost, and (3) facilities relocation cost. The proposed model is coded in Java using NetBeans IDE 8.1 platform. A hypothetical case study with a solution space of 243 solutions was conducted to demonstrate the model’s benefits. The model succeeded in finding the optimal CFL for road segments in under 1,100 milliseconds using an 8 GB RAM, 2.00 GHz machine.

ACS Style

Amr G. Mansour; Mohamed S. Eid; Emad E. Elbeltagi. Optimal Construction Facilities Location Selection for Linear Infrastructure Projects. Computing in Civil Engineering 2019 2019, 1 .

AMA Style

Amr G. Mansour, Mohamed S. Eid, Emad E. Elbeltagi. Optimal Construction Facilities Location Selection for Linear Infrastructure Projects. Computing in Civil Engineering 2019. 2019; ():1.

Chicago/Turabian Style

Amr G. Mansour; Mohamed S. Eid; Emad E. Elbeltagi. 2019. "Optimal Construction Facilities Location Selection for Linear Infrastructure Projects." Computing in Civil Engineering 2019 , no. : 1.

Articles
Published: 01 October 2018 in International Journal of Construction Management
Reads 0
Downloads 0

This paper presents a simultaneous multi-criteria optimization approach for scheduling linear infrastructure projects. The proposed model provides planners with sets of non-dominated alternatives and their corresponding tradeoffs. The associated research methodology includes: (1) developing a resource driven scheduling module; (2) applying a multi-criteria optimization technique to optimize the multi-objective scheduling problem; (3) integrating the proposed model with a commercial project management software; and (4) applying the developed model on two literature-drawn case studies. The developed multi-criteria optimization approach utilizes Genetic Algorithms and Pareto Front sorting. The resulting sets of schedules are based on the multiple inter-conflicting objectives of simultaneously minimizing project duration, minimizing cost, minimizing interruptions, and minimizing unit delivery delays. The results indicate that the proposed approach can explore a greater range of solutions compared to existing models. The developed multi-criteria optimization approach can aid planners with proposing optimal set of schedules.

ACS Style

Mohamed S. Eid; Emad Elbeltagi; Islam H. El-Adaway. Simultaneous multi-criteria optimization for scheduling linear infrastructure projects. International Journal of Construction Management 2018, 21, 41 -55.

AMA Style

Mohamed S. Eid, Emad Elbeltagi, Islam H. El-Adaway. Simultaneous multi-criteria optimization for scheduling linear infrastructure projects. International Journal of Construction Management. 2018; 21 (1):41-55.

Chicago/Turabian Style

Mohamed S. Eid; Emad Elbeltagi; Islam H. El-Adaway. 2018. "Simultaneous multi-criteria optimization for scheduling linear infrastructure projects." International Journal of Construction Management 21, no. 1: 41-55.

Research article
Published: 14 June 2018 in Shock and Vibration
Reads 0
Downloads 0

One of the main driving factors for structures’ evaluation is the foundation settlement. Measuring structures’ settlement in field is costly especially when heavy loads are applied. Settlement prediction models can be used to avoid the high cost of settlement field tests. Four advanced heuristic regression methods are developed and applied in this study to estimate raft foundations’ settlement, namely, multivariate adaptive regression splines (MARS), M5 model tree (M5Tree), generalized regression neural networks (GRNN), and support vector regression (SVR) techniques. Simulation of raft pile foundations is utilized to calculate the settlements of piles under the effect of static and dynamic loads. Previous studies are compared with the newly developed models. The results show that the four models can be used to accurately predict foundations’ settlements in the training stage. Also, the results reveal that the MARS and SVR models performed slightly better than the M5Tree and GRNN models in the testing stage and accordingly can be used to predict foundations’ settlement. The SVR model outperformed other models when few numbers of measurements are available.

ACS Style

Mosbeh R. Kaloop; Jong Wan Hu; Emad Elbeltagi. Pile-Raft Settlements Prediction under Coupled Static-Dynamic Loads Using Four Heuristic Regression Approaches. Shock and Vibration 2018, 2018, 1 -10.

AMA Style

Mosbeh R. Kaloop, Jong Wan Hu, Emad Elbeltagi. Pile-Raft Settlements Prediction under Coupled Static-Dynamic Loads Using Four Heuristic Regression Approaches. Shock and Vibration. 2018; 2018 ():1-10.

Chicago/Turabian Style

Mosbeh R. Kaloop; Jong Wan Hu; Emad Elbeltagi. 2018. "Pile-Raft Settlements Prediction under Coupled Static-Dynamic Loads Using Four Heuristic Regression Approaches." Shock and Vibration 2018, no. : 1-10.

Editorial
Published: 30 May 2018 in Journal of Sensors
Reads 0
Downloads 0
ACS Style

Mosbeh R. Kaloop; Jong Wan Hu; Emad Elbeltagi; Ahmed El Refai. Structural Health Monitoring and Assessment: Sensors and Analysis. Journal of Sensors 2018, 2018, 1 -2.

AMA Style

Mosbeh R. Kaloop, Jong Wan Hu, Emad Elbeltagi, Ahmed El Refai. Structural Health Monitoring and Assessment: Sensors and Analysis. Journal of Sensors. 2018; 2018 ():1-2.

Chicago/Turabian Style

Mosbeh R. Kaloop; Jong Wan Hu; Emad Elbeltagi; Ahmed El Refai. 2018. "Structural Health Monitoring and Assessment: Sensors and Analysis." Journal of Sensors 2018, no. : 1-2.

Conference paper
Published: 01 May 2018 in IOP Conference Series: Earth and Environmental Science
Reads 0
Downloads 0

Quantitative assessment of emissions related to construction projects should be performed during the planning phase of the projects. This is significant to spot the high values of pollution during the construction phase. In this study, a model is developed to estimate pollution resulting from Buildings construction activities. The model calculates the generated pollution for each activity involved in the project as a result of dust, gases and noise emissions. A new index is developed namely Activity Pollution Index (API) which expresses the amount of total pollution for each activity during the project construction phase. Also, the developed model is able to display the resulted total pollution distribution throughout the project life that corresponding to the planned scheduling. An actual case study in an administrative building construction in Egypt is selected to demonstrate the practical use of the proposed model. The results show that the peak and minimum values of total pollution were occurred during the excavation activity and the formwork erections and steel fixing of the second segment of the building with values of API equal to 69 and 2, respectively.

ACS Style

Islam Elmasoudi; Mona G. Ibrahim; Wael Elham Mahmod; Emad Elbeltagi. Developing a New Activity Pollution Index for Emissions Quantitative Assessment in Projects Construction Phase: Case Study of an Administrative Building, Egypt. IOP Conference Series: Earth and Environmental Science 2018, 151, 012018 .

AMA Style

Islam Elmasoudi, Mona G. Ibrahim, Wael Elham Mahmod, Emad Elbeltagi. Developing a New Activity Pollution Index for Emissions Quantitative Assessment in Projects Construction Phase: Case Study of an Administrative Building, Egypt. IOP Conference Series: Earth and Environmental Science. 2018; 151 (1):012018.

Chicago/Turabian Style

Islam Elmasoudi; Mona G. Ibrahim; Wael Elham Mahmod; Emad Elbeltagi. 2018. "Developing a New Activity Pollution Index for Emissions Quantitative Assessment in Projects Construction Phase: Case Study of an Administrative Building, Egypt." IOP Conference Series: Earth and Environmental Science 151, no. 1: 012018.

Journal article
Published: 01 January 2018 in Journal of Computing in Civil Engineering
Reads 0
Downloads 0

In this paper, five models based on evolutionary algorithms (EAs) are introduced and compared for the optimization of the design and rehabilitation of water distribution networks. These EAs include the genetic algorithm (GA), the particle swarm optimization (PSO), the ant colony optimization (ACO), the memetic algorithm (MA), and the modified shuffled frog leaping algorithm (SFLA). A brief description of each algorithm is introduced to explain its application. A methodology is applied for the rigorous comparison of the models in terms of the optimum solution obtained, the number of objective function evaluations corresponding to the optimum solution, the effect of starting seeds on the optimum solution, and the quality of the results. A statistical analysis is carried out and then an efficiency-rate metric is determined to assess the performance of each model. The five EAs are applied to two popular benchmark networks, the two-loop network and the New York tunnels. In addition, the models are applied to a real water distribution network of El-Mostakbal City, Egypt. The results show that the PSO outperformed the other evolutionary algorithms in terms of the efficiency-rate metric and the rapid convergence to the best solution.

ACS Style

Hamdy A. El-Ghandour; Emad Elbeltagi. Comparison of Five Evolutionary Algorithms for Optimization of Water Distribution Networks. Journal of Computing in Civil Engineering 2018, 32, 04017066 .

AMA Style

Hamdy A. El-Ghandour, Emad Elbeltagi. Comparison of Five Evolutionary Algorithms for Optimization of Water Distribution Networks. Journal of Computing in Civil Engineering. 2018; 32 (1):04017066.

Chicago/Turabian Style

Hamdy A. El-Ghandour; Emad Elbeltagi. 2018. "Comparison of Five Evolutionary Algorithms for Optimization of Water Distribution Networks." Journal of Computing in Civil Engineering 32, no. 1: 04017066.

Review
Published: 24 November 2017 in ISPRS International Journal of Geo-Information
Reads 0
Downloads 0

This paper presents the recent development in Structural Health Monitoring (SHM) applications for monitoring the dynamic behavior of structures using the Global Positioning Systems (GPS) technique. GPS monitoring systems for real-time kinematic (RTK), precise point positioning (PPP) and the sampling frequency development of GPS measurements are summarized for time series analysis. Recent proposed time series GPS monitoring systems, errors sources and mitigation, as well as system analysis and identification, are presented and discussed.

ACS Style

Mosbeh R. Kaloop; Emad Elbeltagi; Jong Wan Hu; Ahmed Elrefai. Recent Advances of Structures Monitoring and Evaluation Using GPS-Time Series Monitoring Systems: A Review. ISPRS International Journal of Geo-Information 2017, 6, 382 .

AMA Style

Mosbeh R. Kaloop, Emad Elbeltagi, Jong Wan Hu, Ahmed Elrefai. Recent Advances of Structures Monitoring and Evaluation Using GPS-Time Series Monitoring Systems: A Review. ISPRS International Journal of Geo-Information. 2017; 6 (12):382.

Chicago/Turabian Style

Mosbeh R. Kaloop; Emad Elbeltagi; Jong Wan Hu; Ahmed Elrefai. 2017. "Recent Advances of Structures Monitoring and Evaluation Using GPS-Time Series Monitoring Systems: A Review." ISPRS International Journal of Geo-Information 6, no. 12: 382.

Journal article
Published: 01 September 2017 in Journal of Building Engineering
Reads 0
Downloads 0
ACS Style

Emad Elbeltagi; Hossam Wefki; Saad Abdrabou; Mahmoud Dawood; Ahmed Ramzy. Visualized strategy for predicting buildings energy consumption during early design stage using parametric analysis. Journal of Building Engineering 2017, 13, 127 -136.

AMA Style

Emad Elbeltagi, Hossam Wefki, Saad Abdrabou, Mahmoud Dawood, Ahmed Ramzy. Visualized strategy for predicting buildings energy consumption during early design stage using parametric analysis. Journal of Building Engineering. 2017; 13 ():127-136.

Chicago/Turabian Style

Emad Elbeltagi; Hossam Wefki; Saad Abdrabou; Mahmoud Dawood; Ahmed Ramzy. 2017. "Visualized strategy for predicting buildings energy consumption during early design stage using parametric analysis." Journal of Building Engineering 13, no. : 127-136.

Research article
Published: 19 April 2017 in Shock and Vibration
Reads 0
Downloads 0

This study investigates predicting the pullout capacity of small ground anchors using nonlinear computing techniques. The input-output prediction model for the nonlinear Hammerstein-Wiener (NHW) and delay inputs for the adaptive neurofuzzy inference system (DANFIS) are developed and utilized to predict the pullout capacity. The results of the developed models are compared with previous studies that used artificial neural networks and least square support vector machine techniques for the same case study. The in situ data collection and statistical performances are used to evaluate the models performance. Results show that the developed models enhance the precision of predicting the pullout capacity when compared with previous studies. Also, the DANFIS model performance is proven to be better than other models used to detect the pullout capacity of ground anchors.1. IntroductionLight structures, which are built in open areas, are supported with the ground using small anchors. Such anchors are designed to resist tensile and uplift forces [1–4] and are usually supported at a shallow depth (about 1 m) with small pullout capacity [2, 5, 6]. Therefore, designers rarely put efforts into designing such small ground anchors [5]. In contrast, Shahin and Jaksa [7] introduced new design criteria for small anchors based on advanced prediction models.The numerical prediction models are used to detect the pullout capacity of small ground anchors based on input-output mapping for the in situ data. Shahin and Jaksa [7] utilized 119 anchors’ test data to introduce prediction models. They used the neural networks technique to extract the pullout capacity [7]. In addition, Shahin and Jaksa [2, 6] used artificial neural network (ANN) model for the design of small anchors and they were able to predict the pullout capacity. Samui et al. [5] developed a prediction model based on the least square support vector machine (LSSVM) to detect the pullout capacity of small anchors; and they concluded that the LSSVM performs better than the ANN [5].Nowadays, integrated system identifications are used to design nonlinear input-output prediction models [8, 9]. In general, these models can be divided into multi-input multi-output (MIMO), single-input single-output (SISO), or multi-input single-output (MISO). The selection of the appropriate model depends on the collected data and sensitivity of the input and output variables. Most common integrated identification models are presented in [8] and it is reported that the Hammerstein-Wiener model outperformed other models [8]. Also, it is found that the nonlinear Hammerstein-Wiener model performance is better than the linear one [10]. On the other hand, the adaptive neurofuzzy inference system (ANFIS) is used widely for the designing of prediction’s models; more details on the ANFIS model design and previous studies can be found in [11–14]. The performance of the ANFIS model is better with MISO variables [13, 14]. Arsava et al. [14] introduced a time delayed-ANFIS (DANFIS) prediction model for the control structures, and they found that DANFIS model performance is much better than conventional ANFIS models. Based on the above review, the nonlinear Hammerstein-Wiener (NHW) and DANFIS models can be used to detect the pullout capacity. Therefore, a new model will be developed to detect the pullout capacity, and the results will be compared with ANN [2] and LSSVM [5] models based on Shahin and Jaksa [2] data collection.The objectives of this study are the following: () to examine the capability of the NHW and DANFIS models for predicting small ground anchors pullout capacity; () to compare the performance of developed models with previous studies; and () to study the significance of input variables on pullout capacity of small ground anchor.2. Material and Methods2.1. Prediction ModelsThe MISO prediction models, NHM and DANFIS, are utilized in this study to extract the pullout capacity of small ground anchors. These models are described in the following subsections.2.1.1. Nonlinear Hammerstein-Wiener ModelThe NHW model is an integrated prediction model using nonlinear and linear transforming functions [8]. The model includes input and output nonlinear functions and linear model connected the input and output functions [10]. The nonlinear one-layer sigmoid and wavelet networks, saturation, one-dimension polynomial, and piecewise functions are used for the input and output transforming [15]. In addition, the similar polynomial functions (B and F) are defined in the time-shift operator. Figure 1 represents the NHW model diagram. To predict the pullout capacity , the input variables , and transforming results and are utilized and calculated. More details for the NHW model can be found in [16, 17].Figure 1: MISO-NHW model diagram structure.In this study, four input variables are used to predict the pullout capacity of a MISO model. The trail and errors method is used to select the input and output nonlinearity functions. Therefore, the nonlinearity input function is applied to each input variable , and the output of each variable can be calculated as follows:The linear output block is a summation of the inputs as follows:where is the number of inputs for a MISO model and and are polynomials defined in the time-shift operator . The model order is chosen based on zero order and pole order , with delays set to zero and selected as 4. The zero-pole orders are obtained using the prediction error method. As such, the pullout capacity can be calculated as follows:In this paper, the prediction trials were performed with the Matlab command nlhw of the system identification toolbox. Moreover, the models were obtained using model error in which the minimized criterion is the square of the errors, normalized by the length of the data set. In addition, the models performances are evaluated.2.1.2. Delay Inputs for the Adaptive Neurofuzzy Inference System (DANFIS)The time delayed adaptive neurofuzzy inference system (DANFIS) is proposed in [14] to predict the complex nonlinear behavior of smart structures. In this paper, the DANFIS model is developed to predict the pullout capacity of small ground anchors based on MISO parameters. Figure 2 illustrates the developed model using four input data sets and one delay for the output variable. The ANFIS model consists of a set of fuzzy rules with appropriate membership functions to generate the stipulated input-output pairs in the solution of uncertain and ill-defined systems [12, 14, 18, 19]. As presented in Figure 2, the ANFIS model contains five layers that are the input, input membership function (MF), rules list, output MF, and the output layers. Therefore, it is important to define the types and the values of MF for each input variable. Figure 2 shows two MFs for each variable, as shown in the input MF layer.Figure 2: MISO-DANFIS model diagram structure.The process of the ANFIS model can be found in [14, 18]. As presented in Figure 2, the ANFIS model can be used for mapping the nonlinear MISO variables [20]. In this case, the nonlinear MISO mapping model can be expressed as follows [14, 20]:where are the input variables, is the model output (pullout capacity), is the model error, is a scalar nonlinear mapping function, and the time delay is represented by the term . In this study, four input variables are used and the time delay is assigned a value of one. In general, the if-then rules for the ANFIS model depend on the number of MFs. For each rule, the ANFIS fuzzy model of Takagi and Sugeno (TS) [21] can be applied as follows [18].Assuming first that , while ; is the number of measurements; and , as presented in Figure 2, the model rule for the four inputs can be processed as follows.Rule is as follows: if is , is , is , is , and is , thenwhere are the input variables, is the delayed output variable (pullout capacity), is the output of the TS fuzzy system, and are the consequent parameters [18]. Therefore, as shown in Figure 2, the output of the five layers can be presented as follows:The Output of the Input MF Layer where , , , , and are the MFs for the input variables of the model. The MF shape is divided into continuous and piecewise differentiable functions with normalized output [12, 18]. Triangular MFs are used which can be presented for the first input () as follows (the same relation can be found for each input variable):where the parameters a, b, and c are the triangular MF values. These parameters can be called the premise parameters as they are the adjustable parameters in the premise part. The Output of the Rule Layer. This layer has two processes; the first is calculating the firing strength of each fuzzy rule, as follow:The second is normalizing the firing strength, as follows:where, is the number of input variables. The Output of the Output MF Layer. In this layer, the node functions are applied with the previous layer output; the first-order TS model is used and the output of this layer can be expressed as follows:The Output of the Output Layer. As the last step, the output of this layer is calculated as follows:Based on (4) and (11), to estimate the element , the DANFIS output is calculated as follows [14, 22]: 2.2. Case StudyTo evaluate the developed models, the field data of 119 anchors are derived using an in situ test database from Shahin and Jaksa [2]. Figure 3 represents the data points and parameters that are considered in this study. As presented in Figure 3, the input variables are the equivalent anchor diameter , embedment depth , average cone resistance along the embedment depth, average sleeve friction along the embedment depth, and installation technique (IT) and the anchor pullout capacity, , is the output. The installation techniques used in this case are static and dynamic cases which are represented by 1 and 2, respectively, as shown in Figure 3. The anchor’s types and properties and the anchor’s tests process are discussed and presented in

ACS Style

Mosbeh R. Kaloop; Jong Wan Hu; Emad Elbeltagi. Predicting the Pullout Capacity of Small Ground Anchors Using Nonlinear Integrated Computing Techniques. Shock and Vibration 2017, 2017, 1 -10.

AMA Style

Mosbeh R. Kaloop, Jong Wan Hu, Emad Elbeltagi. Predicting the Pullout Capacity of Small Ground Anchors Using Nonlinear Integrated Computing Techniques. Shock and Vibration. 2017; 2017 ():1-10.

Chicago/Turabian Style

Mosbeh R. Kaloop; Jong Wan Hu; Emad Elbeltagi. 2017. "Predicting the Pullout Capacity of Small Ground Anchors Using Nonlinear Integrated Computing Techniques." Shock and Vibration 2017, no. : 1-10.

Journal article
Published: 29 November 2016 in ISPRS International Journal of Geo-Information
Reads 0
Downloads 0

Global Positioning System (GPS) structural health monitoring data collection is one of the important systems in structure movement monitoring. However, GPS measurement error and noise limit the application of such systems. Many attempts have been made to adjust GPS measurements and eliminate their errors. Comparing common nonlinear methods used in the adjustment of GPS positioning for the monitoring of structures is the main objective of this study. Nonlinear Adaptive-Recursive Least Square (RLS), extended Kalman filter (EKF), and wavelet principal component analysis (WPCA) are presented and applied to improve the quality of GPS time series observations. Two real monitoring observation systems for the Mansoura railway and long-span Yonghe bridges are utilized to examine suitable methods used to assess bridge behavior under different load conditions. From the analysis of the results, it is concluded that the wavelet principal component is the best method to smooth low and high GPS sampling frequency observations. The evaluation of the bridges reveals the ability of the GPS systems to detect the behavior and damage of structures in both the time and frequency domains.

ACS Style

Mosbeh R. Kaloop; Jong Wan Hu; Emad Elbeltagi. Adjustment and Assessment of the Measurements of Low and High Sampling Frequencies of GPS Real-Time Monitoring of Structural Movement. ISPRS International Journal of Geo-Information 2016, 5, 222 .

AMA Style

Mosbeh R. Kaloop, Jong Wan Hu, Emad Elbeltagi. Adjustment and Assessment of the Measurements of Low and High Sampling Frequencies of GPS Real-Time Monitoring of Structural Movement. ISPRS International Journal of Geo-Information. 2016; 5 (12):222.

Chicago/Turabian Style

Mosbeh R. Kaloop; Jong Wan Hu; Emad Elbeltagi. 2016. "Adjustment and Assessment of the Measurements of Low and High Sampling Frequencies of GPS Real-Time Monitoring of Structural Movement." ISPRS International Journal of Geo-Information 5, no. 12: 222.