ahmed elhattab , phd , se , pe
Senior Engineer II at SC Solutions
senior engineer ii sc solution
phd , pe structural engineer 10+ year experience . experience span multidisciplinary area including design structure , dynamic analysis , soil structure interaction , vehicle/bridge interaction dynamic , computational fluid dynamic , linear/nonlinear finite element analysis , implicit/explicit dynamic analysis , bridge structure , structural health monitoring , sensor design signal processing . project portfolio includes 40+ engineering project focused heavy industrial facility infrastructure condition assessment . research project funded nsf , usdot , utc , nchrp . research oriented towards developing new insight structural condition assessment non-destructive evaluation .
SC Solutions
https://www.linkedin.com/company/sc-solutions
Sacramento, California, United States
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Senior Engineer II
Southern Company
https://www.linkedin.com/company/southern-company
Birmingham, Alabama Area
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Structural Engineer
University of Alabama at Birmingham
https://www.linkedin.com/company/uab
Birmingham, Alabama
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Graduate Research Assistant
PROC-Global
https://www.linkedin.com/company/proctal
Egypt
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Structural Engineer
Civil Consulting
https://www.linkedin.com/company/civil-consulting
Alexandria, Egypt.
Structural Engineer
Doctor of Philosophy - PhD
Structural Engineering
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University of Alabama at Birmingham
https://www.linkedin.com/school/uab/
Master of Science - MS
Structural Engineering
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University of Alabama at Birmingham
https://www.linkedin.com/school/uab/
Bachelor’s Degree
Civil Engineering
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Alexandria University
https://www.linkedin.com/school/alexandria-university/
American Society of Nondestructive Testing (ASNT)
Member
American Society of Civil Engineers (ASCE)
Memeber
American Society of Mechanical Engineers
Member
Smartphone MEMS (Micro Electrical Mechanical System) accelerometers have relatively low sensitivity and high output noise density. Therefore, it cannot be directly used to track feeble vibrations such as structural vibrations. This article proposes an effective increase in the sensitivity of the smartphone accelerometer utilizing the stochastic resonance (SR) phenomenon. SR is an approach where, counter-intuitively, feeble signals are amplified rather than overwhelmed by the addition of noise. This study introduces the 2D-frequency independent underdamped pinning stochastic resonance (2D-FI-UPSR) technique, which is a customized SR filter that enables identifying the frequencies of weak signals. To validate the feasibility of the proposed SR filter, an iPhone device is used to collect bridge acceleration data during normal traffic operation and the proposed 2D-FI-UPSR filter is used to process these data. The first four fundamental bridge frequencies are successfully identified from the iPhone data. In parallel to the iPhone, a highly sensitive wireless sensing network consists of 15 accelerometers (Silicon Designs accelerometers SDI-2012) is installed to validate the accuracy of the extracted frequencies. The measurement fidelity of the iPhone device is shown to be consistent with the wireless sensing network data with approximately 1% error in the first three bridge frequencies and 3% error in the fourth frequency. View Full-Text
Extraction of Bridge Fundamental Frequencies Utilizing a Smartphone MEMS Accelerometer
MDPI
https://www.mdpi.com/1424-8220/19/14/3143
Natural Frequencies of structures is an elegant intrinsic property that is essential for many Civil Structural applications, as Structural Health Monitoring and Simulation Modeling. The physically tangible relation between the frequency of the structures and its dynamic characteristics was the impetus for using different time/frequency based methods to quantify this fundamental property. Unfortunately, the disruption effect of noise requires incorporating advanced sensors, that provide signals with a low noise-intensity, to accurately identify the fundamental frequencies of the structure. This article solves this bottleneck via exploiting the Stochastic Resonance (SR) phenomena to extract the fundamental frequencies of a bridge using an acceleration recorded by a conventional portable sensor as the sensor implemented in small portable accelerometer. The portable accelerometer device has an M9 motion coprocessor designed mainly for tracking human activities. Human activities have an exaggerated amplitude when it is compared to the structural responses. Therefore, if an iPhone device is used to record the response of the structure (for example a bridge) the structure response will be swamped by severe surrounding noise because of its small amplitude. Therefore, in this vein, the SR phenomena has been employed to use rather than suppress the noise to magnify the feeble bridge response in the recorded acceleration and hence identify the corresponding frequency. The fidelity of the proposed approach has been verified using the data of a field experiment. The bridge frequencies are identified first using conventional vibration analysis, thereafter, the portable accelerometer has been attached to the bridge rail to record the bridge vibration under the passing traffic. The recorded data has been processed using a new Developed Underdamped Pinning Stochastic Resonance (DUPSR) technique to quantify the bridge frequency.
Bridge Monitoring Utilizing Smart Portable Sensing System
ASNT
https://ndtlibrary.asnt.org/en/2018/BridgeMonitoringUtilizingSmartPortableSensingSystem.aspx
Recently, drive-by bridge inspection has attracted increasing attention in the bridge monitoring field. A number of studies have given confidence in the feasibility of the approach to detect, quantify, and localize damages. However, the speed of the inspection truck represents a major obstacle to the success of this method. High speeds are essential to induce a significant amount of kinetic energy to stimulate the bridge modes of vibration. On the other hand, low speeds are necessary to collect more data and to attenuate the vibration of the vehicle due to the roughness of the road and, hence, magnify the bridge influence on the vehicle responses. This article introduces Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR) as a new technique, which possesses the ability to extract bridge dynamic properties from the responses of a vehicle that passes over the bridge at high speed. Stochastic Resonance (SR) is a phenomenon where feeble information such as weak signals can be amplified through the assistance of background noise. In this study, bridge vibrations that are present in the vehicle responses when it passes over the bridge are the feeble information while the noise counts for the effect of the road roughness on the vehicle vibration. UPSR is one of the SR models that has been chosen in this study for its suitability to extract the bridge vibration. The main contributions of this article are: (1) introducing a Frequency Independent-Stochastic Resonance model known as the FI-UPSR and (2) implementing this model to extract the bridge vibration from the responses of a fast passing vehicle. View Full-Text
Drive-By Bridge Frequency Identification under Operational Roadway Speeds Employing Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR)
Sensors
https://www.mdpi.com/1424-8220/18/12/4207
Recently, drive-by bridge inspection has attracted increasing attention in the bridge monitoring field. A number of studies have given confidence in the feasibility of the approach to detect, quantify, and localize damages. However, the speed of the inspection truck represents a major obstacle to the success of this method. High speeds are essential to induce a significant amount of kinetic energy to stimulate the bridge modes of vibration. On the other hand, low speeds are necessary to collect more data and to attenuate the vibration of the vehicle due to the roughness of the road and, hence, magnify the bridge influence on the vehicle responses. This article introduces Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR) as a new technique, which possesses the ability to extract bridge dynamic properties from the responses of a vehicle that passes over the bridge at high speed. Stochastic Resonance (SR) is a phenomenon where feeble information such as weak signals can be amplified through the assistance of background noise. In this study, bridge vibrations that are present in the vehicle responses when it passes over the bridge are the feeble information while the noise counts for the effect of the road roughness on the vehicle vibration. UPSR is one of the SR models that has been chosen in this study for its suitability to extract the bridge vibration. The main contributions of this article are: (1) introducing a Frequency Independent-Stochastic Resonance model known as the FI-UPSR and (2) implementing this model to extract the bridge vibration from the responses of a fast passing vehicle
Drive-By Bridge Frequency Identification under Operational Roadway Speeds Employing Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR)
MDPI
https://www.mdpi.com/1424-8220/18/12/4207
Recently, the concept of “drive-by” bridge monitoring system using indirect measurements from a passing vehicle has been rapidly developed. Most of the methods proposed under this system utilize the dynamic characteristics of the objective bridge as an indicator for estimating its condition, such as the natural frequency of bridges. The natural frequency is generally computed applying Fast Fourier Transform (FFT). However, it has been demonstrated that the estimated frequency resolution of FFT for roadways operating speed is too low to be able to detect the frequency drop caused by the degradation of the bridge structural integrity. This paper introduces a new extracting frequency technique based on Hilbert Transform (HT) that is not restrict to frequency resolution and can, therefore, detect bridge damages represented as changing the fundamental frequency of the bridge. The paper will implement this approach using an implicit Vehicle-Bridge Interaction (VBI) algorithm to simulate the passage of the inspection vehicle over the bridge. The acceleration history of vehicle are processed using FFT and band-filter technique to obtain the component response associated with bridge frequencies. Then these signals are employed with HT to refine the bridge frequency so as to assess the bridge condition.
Utilizing Hilbert Transform to Assess the Bridge Health Condition
ICVRAM ISUMA UNCERTAINTIES  conference
https://www.researchgate.net/publication/325253931_Utilizing_Hilbert_Transform_to_Assess_the_Bridge_Health_Condition
Bridge structures are subjected to continuous degradation due to excessive traffic, hazardous events and environmental effects, which elevates the importance of monitoring their structural integrity. Recently, there is a tendency towards using an instrumented vehicle for monitoring bridge structures. This technique is known by ‘drive-by bridge inspection’. This paper introduces a novel technique in the drive-by bridge inspection, by using the acceleration histories for a non-specialized truck to back-derive the bridge deformation under the truck axles. The method will be verified using field experimental data for a real life bridge under different loading conditions. The paper first presents the field test setup. Then, it demonstrates the process of building a calibrated theoretical vehicle model for the inspection truck. After that, it introduces the bridge deformation calculation algorithm, which will be used to extract the bridge deformation under different loading scenarios. The results shows a distinguish difference between bridge deformation for different loading cases. Thus, the same concept can be applied to identify bridge structural degradation, by monitoring the changes in the bridge deformation. The approach uses only the truck measurements, which makes the concept so far cost effective comparing to traditional bridge monitoring techniques.
Monitoring the Structural Integrity of the Bridges Utilizing Non-specialized Instrumented Vehicle: Field Demonstration
Transportation Research Board 97th Annual MeetingTransportation Research Board
https://trid.trb.org/view/1495801
Bridge structures are susceptible to devastating failures ascribing to the continuous strength reduction over time, as well as the unprecedented increase in freight volumes. Therefore, understanding the dynamic response of bridges due to moving traffic, specifically heavy trucks, has attracted the interest of the highway engineers. To this end, Vehicle Bridge Interaction (VBI) modelling has been adopted as a reliable and effective approach to mimic bridge vibrations under transit traffic. The decoupled VBI modelling is based upon solving the vehicle and the bridge equations of motion separately, by equating the contact forces between the vehicle and the bridge at each time step. The equations of motion can be solved either implicitly or explicitly. Implicit analysis directly solves for the displacement vector {x}, which consequently requires calculation of inverse of stiffness matrix. Whilst explicit analysis solves for the acceleration vector {x} by inverting the mass matrix. Most of VBI algorithms adopt an implicit solver, however, the implicit analysis is adequate to simulate static and quasi-static responses which is not representative of the dynamic nature of the truck and bridge vibrations in the field. This article is devoted to illuminate the difference between explicit and implicit solvers in modelling the VBI problems.
The Implication of Analysis Module on Vehicle Bridge Interaction Modelling
Juniper Publishers
https://juniperpublishers.com/cerj/CERJ.MS.ID.555600.php
In recent years, the concept of bridge monitoring using indirect measurements from a passing vehicle has been rapidly developed. This concept is known as “drive-by bridge inspection”. Most of the methods proposed under this approach utilize the dynamic characteristics of the bridge as an indicator of damage, such as the natural frequency of the bridge. The natural frequency is often estimated using fast Fourier transform (FFT). However, FFT has a low frequency resolution at the condition of higher velocity of a passing vehicle; therefore, it is not appropriate to be used to monitor the frequency change caused by the degradation of the bridge structural integrity. This paper introduces a new frequency identification technique based on wavelet analysis. Wavelet transform is characterized by its high-frequency resolution and can, therefore, be used to visualize the bridge damage represented as changing the fundamental frequency of the bridge. The paper will implement this approach using an implicit Vehicle-Bridge Interaction (VBI) algorithm to simulate the passage of the inspection vehicle over the bridge. The acceleration signals are then processed using wavelet analysis to extract the bridge frequency. In addition, the study will investigate the use of a subtracted signal from two consecutive axles. The latter point has the advantage of substantially removing the effect of the road roughness from the recorded acceleration history.
“Drive-by’’ bridge frequency-based monitoring utilizing wavelet transform
Springer
https://link.springer.com/article/10.1007/s13349-017-0246-3
Bridges are a very critical part of a country’s infrastructure and many uncertainties surround important factors determining the serviceability and deterioration of bridges, thus, they require continuous monitoring to ensure their functionality. Several damage indicators have been used for detecting the bridge status, such as the change in bridge natural frequency and bridge apparent profile. In this paper, the time history curvature under a passing vehicle is introduced as an alternative bridge damage indicator. The time history curvature for a bridge is the change in slope per unit length of distance along the bridge with respect to time. The result of time history curvature in moving force over a beam simulation shows the improvement of accuracy on spotting the location of the bridge damage. The bridge is represented as 1D Euler–Bernoulli beam element. Two bridge damage models are used in this research.
Bridge Curvature for Detecting Bridge Damage Location
ASNT
https://ndtlibrary.asnt.org/2017/BridgeCurvatureforDetectingBridgeDamageLocation
Bridge structures are subject to continuous degradation, which requires an ongoing screening to give an early warning if the bridge becomes unsafe. In recent years, many authors have investigated a shift of the instrumentation from the bridge to a passing vehicle to collect indirect measurements for the bridge responses. This approach is known by drive-by bridge inspection. This paper introduces a new method in the drive-by bridge inspection concept which employs acceleration measurements of a non-specialized vehicle to identify the change in the bridge responses due to structural damage. Two damage indices are included in the study, the vehicle acceleration spectra and the change in the bridge displacement. The paper will use an explicit approach for solving the Vehicle-Bridge Interaction (VBI) problem to give a more accurate representation of the truck/bridge interaction. The VBI problem will be solved using LS-Dyna Finite Element Analysis (FEA) program. The bridge is represented by discretized one-dimensional (1D) FE beam elements, and by discretized two-dimensional (2D) plate bending elements. Damage is defined in this study as a change in the damping ratio and/or gradual decrease in structural stiffness. Two vehicle models are used in the study, the two-degree-of-freedom quarter car model and the four-degree-of-freedom half car model. Both smooth and rough profiles are considered in the study.
Drive-by Bridge Damage Detection Using Non-specialized Vehicle
ASNT
https://ndtlibrary.asnt.org/2017/DrivebyBridgeDamageDetectionUsingNonspecializedVehicle
Bridges require continuous screening to ensure their structural integrity. Recently, authors have studied the feasibility of using measurements from a truck equipped with sensors to determine the damage level in the structure of the bridge. This technique is known as “Drive-by Bridge Inspection”. Most of research conducted in this area focused on the processing of the recorded signal to extract the bridge modal properties. This paper presents an alternative method of using the truck measurements to calculate the change in the bridge deformation due to structural damages instead of investigating the bridge modal values. The study uses the Inverse Dynamics Optimization Algorithm to calculate the change in the bridge displacement. A half car model with four degrees of freedom is used to represent the inspection truck. The solution for the Vehicle Bridge Interaction (VBI) is done using the LS-Dyna FEA program. A road roughness class ‘A’ is used to represent the road roughness heights.
Drive-by Bridge Inspection Using Inverse Dynamics Optimization Algorithm
ASNT
https://ndtlibrary.asnt.org/2017/DrivebyBridgeInspectionUsingInverseDynamicsOptimizationAlgorithm
Bridge structures are important infrastructure facilities on the transport network. They are exposed to frequent loads by passing traffic, which affects their structural health condition over time. Therefore, they require periodic monitoring to identify the extent of damage and hence the safety of the road network facility. Conventional Structural Health Monitoring requires direct measures from the bridge, making these methods very expensive and difficult to apply to a large number of bridges. Thus, many researchers have tend to shift the instrumentation to a passing vehicle and use the vehicle measurements to determine the structural health condition of the bridge, which becomes known by 'drive-by bridge inspection'. This article investigate the feasibility of the drive-by bridge inspection technology in field environment. The article is an extension for an intensive theoretical study done by the authors about using non-specialized truck measurements in calculating the change in the bridge displacement due to structural damages. First, the article will introduce the environment of the field experiment and the devices used to measure the vehicle and the bridge vibration. Then it will demonstrate the process of building an equivalent vehicle model for the inspection truck. Lastly, the study uses the equivalent vehicle model to calculate the bridge displacement under several testing scenarios simulates a damage to structure of the bridge.
Field Verification for Drive-by Bridge Monitoring using Non-specialized Inspection Vehicle
ASNT
https://ndtlibrary.asnt.org/2017/FieldVerificationforDrivebyBridgeMonitoringusingNonspecializedInspectionVehicle
Bridges are an integrated part of the transportation infrastructure, which usually applied to severe working environments. Thus, bridges require a continuous screening for their structural health. Recently, there has been an intensive work in the field of monitoring the structural degradation of the bridge structures, yet the developed approaches focus on identifying the existence of the damage with no clue about the damage severity or location. This paper introduces the use of the Frequency Domain Decomposition for the identification of the damage severity and extent. The Frequency Domain Decomposition is used to estimate the mode shape of the bridge using a few measurements on the bridge structure. The differences in the mode shapes between the healthy and damaged states of the bridge are used to identify the damage location and extent. The approach will be verified numerically under the presence of random noise in the input signal. The approach will be extended for a two-dimensional steel frame. The simulation of the vehicle-bridge interaction and the dynamic simulation of the steel structure are performed in MATLAB.
Identifying Localized Bridge Damage Using Frequency Domain Decomposition
ASNT
https://ndtlibrary.asnt.org/2017/IdentifyingLocalizedBridgeDamageUsingFrequencyDomainDecomposition
Bridges as a key component of road networks require periodic monitoring to detect structural degradation for early warning. In term of maintaining the bridge safety, it is essential to estimate the damage location and extent. This paper hypothetically investigates employing the wavelet transform to analysis the signal of a vehicle/bridge system to localize and estimate the damage severity. The paper investigated the feasibility of using direct measurements from the bridge system, in compare with using indirect measurements from a crossing inspection vehicle. The study utilizes an implicit Vehicle-Bridge Interaction (VBI) algorithm to simulate the passage of the instrumented vehicle over the bridge to generate the signal; then the signals are processed using Wavelet Transform. The study found that using the indirect vehicle measurements is more sensitive to bridge damage since the vehicle acts as a moving sensor over the bridge. Further, the paper shows promising results for damage detection using the bridge displacement responses, if the static component of the displacement is removed from the recorded displacement history.
Wavelet Based Damage Assessment and Localization for Bridge Structures
ASNT
https://ndtlibrary.asnt.org/2017/WaveletBasedDamageAssessmentandLocalizationforBridgeStructures
Recently in the area of bridge health monitoring, there is a shift towards the use of indirect measurements of a passing vehicle to assess the structural integrity of bridge structures, which is known as “Drive-by Bridge inspection.” This approach is based on determining the dynamic characteristics of the bridge using the vehicle responses, such as bridge frequencies, bridge mode shapes, and even bridge stiffness and damping. The change in these characteristics over a period of time reflects the level of deterioration of the bridge’s health condition. This article introduces a brief discussion on the development of this field of research since it was revealed. The article addresses the prominent studies in this domain, while some other work is not included for the sake of brevity in the paper. This article is a good starting point for those interested in researching this topic.
Drive-by Bridge Damage Monitoring: Concise Review
Juniper Publishers
https://juniperpublishers.com/cerj/pdf/CERJ.MS.ID.555555.pdf
Bridge structures are subject to continuous degradation, which requires an ongoing screening to give an early warning if the bridge becomes unsafe. In recent years, many authors have investigated a shift of the instrumentation from the bridge to a passing vehicle to collect indirect measurements for the bridge responses. This approach is known by ‘drive-by’ bridge inspection. This paper introduces a new method in the drive-by bridge inspection concept which employs acceleration measurements of a non-specialized vehicle to identify the change in the bridge responses due to structural damage. Two damage indices are included in the study, the vehicle acceleration spectra and the change in the bridge displacement. The paper will use an explicit approach for solving the Vehicle-Bridge Interaction (VBI) problem to give a more accurate representation of the truck/bridge interaction. The VBI problem will be solved using LS-Dyna Finite Element Analysis (FEA) program. The bridge is represented by discretized one-dimensional (1D) FE beam elements, and by discretized two-dimensional (2D) plate bending elements. Damage is defined in this study as a change in the damping ratio and/or gradual decrease in structure stiffness. Two vehicle models are used in the study, the two-degree-of-freedom quarter car model and the four-degree-of-freedom half car model. Both smooth and rough profiles are considered in the study.
Drive-by bridge damage detection using non-specialized instrumented vehicle
IOS press
http://content.iospress.com/articles/bridge-structures/brs106
Recently, there has been a shift in emphasis in bridge monitoring from instrumentation of the bridge to instrumentation of a passing vehicle, known by “drive-by bridge inspection”. This paper introduces a new method of identifying bridge damage using an instrumented truck; specifically using the truck acceleration histories to calculate changes in the “bridge displacement profile” which is shown to be sensitive to structural damage. The study includes three different bridges modeled as 1D FE beam elements and 2D FE plate elements. The simulation of the vehicle–bridge interaction is implemented in MATLAB. The truck is represented as a simple quarter car model crossing over a rough profile. The approach is also numerically tested for local damage in the bridge plate model. Finally, there is a study of sensitivity to signal noise, corrupted truck properties, initial conditions and transverse vehicle position.
Drive-by bridge damage monitoring using Bridge Displacement Profile Difference
Springer
http://rd.springer.com/article/10.1007/s13349-016-0203-6
Bridge structures are subjected to continuous degradationdue to envi-ronmental effect  and  excess  loading. Monitoring  of  bridges  is  a  key  part of any maintenance  strategy as  it can  give an early  warning if the  bridge becomes  un-safe.  This  paper  theoretically  assesses  the  ability  of  vehicle  fitted  with  accel-erometers  to  detect  damage  in  the  bridge.  Damage  is  defined  in  this  study  as change  in  damping  ration  and  loss  in  structure  stiffness.  Two  car  models  are used in this investigation. The first is the two degree of freedom quarter car mod-el, while the second is four degree of freedom half car model. The bridge is mod-eled as a simply supported beam. Both car and bridge are modeled using Finite Element  Analysis  LS-DYNAprogram.  Both  smooth  and  rough  profiles  are  used in the study
Drive-by Bridge Damage Detection using Apparent Profile
CICM
https://www.researchgate.net/publication/305378662_Drive-by_Bridge_Damage_Detection_using_Apparent_Profile
University of Alabama at Birmingham
Second Place Winner of 3MT competition
The University of Alabama at Birmingham
School of Engineering Doctoral Student Dean's Award
Selected as the Outstanding Graduate Student Engineer for the School of Engineering from five departmental nominees.
The University of Alabama at Birmingham
Outstanding Graduate Student Engineer for the School of Engineering
For excellence as a graduate student and as research assistant in the Civil Engineering Department
The University of Alabama at Birmingham
Outstanding Student of the Year in the Civil Engineering Department
For graduation with Distinction degrees during the five years of education in the Faculty of Engineering
Alexandria University
Degree of Honor and Excellence
For achieving A grade in  Hydraulics II course in a class of 882 students
Alexandria University, Faculty of Engineering
Alexandria University- Dr. Monir Kansoh - Excellence Achievement in Hydraulics
For achieving A grade in  Hydraulics II course in a class of 882 students
Alexandria University, Faculty of Engineering
Alexandria University- Dr. Monir Kansoh - Excellence Achievement in Hydraulics
Advanced Geo-technical Engineering
CE590
Advanced Mechanics
CE520
Advanced Reinforced Concrete
CE655
Advanced Structural Analysis
CE562
Advanced Structural Steel
CE750
Applied Finite Element Analysis
MSE668
Bridge Engineering
CE568
Drive-by Bridge Inspection
CE791
Dynamic Bridge Safety Simulation
CE 691
Engineering Statistics
CE791
Foundation Engineering
CE526
Fracture Mechanics
ME690
Intro to CFD Basics
ME521
Intro to Finite-Element Method
CE561
Simulation Bridge Vehicle
CE791
Structural Dynamics
CE564
Wind and Seismic Loads
CE567
Design of R.C. Structures For Earthquake Resistance
02542
Finite Element
02610
Introduction to Fracture Mechanics
02645
Limit state design of reinforced concrete structures
02647
Numerical Methods For Solving Soil Problems
02622
Tall Concrete Buildings
02650
Devised new structural system for the feeder structure at low voltage side (15kV, 23kV and 46kV). The new design saved $30,000 (60% of the total cost) per feeder comparing to the old design.
Low voltage substation feeders
Constructed a design manual (similar to the AISC Steel Construction manual) that includes capacities for standard connections which are used by the Southern Company engineers.
Connection Design Manual
Simulated the Federal Motor Vehicle Safety Standard (FMVSS) Guard Test Procedures to test a new rear guard design for Southern Company Utility trucks. FE Dynamic model was developed using ANSYS To simulate the FMVSS rear guard test.
Utility Truck Guard Rail Design
Performed an extensive analysis for existing column base connections and proposed new designs to save the existing utilities which represents over $2.3B of the Southern company assets
Column Base Connection Study
This proposal is for research on the Mobile Automated Rovers Fly-By (MARS-FLY) for Bridge Network Resiliency. Bridges are often in remote locations and the cost of installing electricity and a data acquisition system in hundreds of thousands of bridges is prohibitive. The MARS-FLY project will develop a cyber-physical system (CPS) designed to monitor the health of highway bridges, control the loads imposed on bridges by heavy trucks, and provide visual inspectors with quantitative information for data-driven bridge health assessment requiring no electricity and a minimum of data acquisition electronics on site. For fly-by monitoring, GPS-controlled auto-piloted drones will periodically carry data acquisition electronics to the bridge and download the data from the sensors at a close range. Larger Imaging drones carrying infrared (IR) cameras will be used to detect detail damages like concrete delamination. 

The research objectives will be accomplished first, by wireless recharging of remote sensor motes by drone to enhance the sensor operational lifetime whereas wireless recharging of drone battery will extend the operational efficiency, payload, and drone range. The novel multi-coil wireless powering approach will provide an investigation of an engineered material i.e. metamaterial with the resonant link to enhance the power level and link distance, otherwise unachievable. Next, by a major scientific breakthrough in the utilization of small quantities of low quality sensor data and IR images to determine damage information at all levels: detection of a change in behavior, location, and magnitude; streamlining of reliability analysis to incorporate the new information of damage into the bridge's reliability index based on combined numerical and probabilistic approaches such as Ensemble Empirical Mode Decomposition with the Hilbert Transform; and finally detection of nonlinearities in the signals in a Bayesian Updating framework.
Mobile Automated Rovers Fly-By (MARS-FLY) for Bridge Network Resiliency
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1645863&amp;HistoricalAwards=false
This grant provides funding for research on the Next Generation Bridge Weigh-in-Motion (B-WIM) system. This system addresses the bridge safety problem using a two-fold approach: the control of overloaded trucks and the safety assessment/monitoring of bridges. The research will be based on the mathematical modeling of a coupled system of differential equations that represent the dynamic interaction of a moving truck with a bridge while accounting for uncertainties that are due to the unknown road profile and dynamic truck properties. The road profile can be measured but, as it is likely to change over time and the exact transverse location of the truck in its lane is unknown, there is a stochastic component of the system. Therefore, the spring and damping properties of the truck tire and suspension will be treated probabilistically, using a Bayesian Updating approach for the properties of the truck fleet. The difficulties associated with this system when it detects the presence of other smaller vehicles that interfere with the signal will be addressed using a new field of statistics known as the "Classification with a Reject Option". In this way, fleets of vehicles can be simulated to represent a range of situations and the simulations will be complemented by independent field trials for validation purposes.

This project seeks to develop a bridge monitoring and protection system that is effective without being manpower intensive. This project, jointly funded by UK and Ireland funding agencies that leverage the NSF investment, will generate a broad spectrum of spin-off technologies. The potential payoff of this program could be the rapid technology insertion into existing bridge maintenance systems that are needed for much of the bridge stock in the USA and Europe. Moreover, wide deployment of this system has the potential to greatly improve the effectiveness of overload enforcement and to increase road safety for all users.
Developing Bridge Weigh-in-Motion (B-WIM) Health Monitoring Systems for Bridge Infrastructure Safety
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1100742
In this project, a wireless sensor network will be investigated for installation on a heavy truck to record the dynamic response of the truck as it crosses a bridge mounted with BWIM+NDE devices. The sensors installed in the vehicle include accelerometers to measure vibration and gyroscopes to capture vehicle pitching motion. As the instrumented vehicle approaches the bridge, BWIM+NDE system wirelessly establishes communication with wireless sensors on the vehicle to synchronize time and initiate data collection. As the truck crosses the bridge, the wireless sensors on the truck transmit vibration and pitching data to the wireless BWIM+NDE server for automatic integration with bridge response data. Experimental validation of the proposed wireless system will be performed both in the lab and in the field.
Field Validation of a Drive-By Bridge Inspection System with Wireless BWIM + NDE Devices
http://www.gti.gatech.edu/pi/field-validation-drive-bridge-inspection-system-wireless-bwim-nde-devices
This study will focus on adjusting bridge rail design procedures to conform with the recently revised crash testing guidelines, MASH. This study will attempt to develop a better method for using dynamic impact loads to design bridge rail and cantilever deck systems. The new procedures will eliminate the problems associated with the use of dynamic forces in quasi-static design methods that currently produce oversized bridge railings and excessive deck thicknesses when accurate peak dynamic loads are used in the existing design method.
BRIDGE RAIL DESIGN PROCEDURES
http://www.nctspm.gatech.edu/pi/bridge-rail-design-procedures
We take electrical power for granted, but delivering it to a light switch requires massive investment, programme of work, and in many cases huge projects to be undertaken.
Proc Global’s team has been involved in power generation projects and the associated distribution services that require extensive planning and environmental approval.
Proc Global has supported a range of clients, developers and contractors, in forming programmes of works, and supporting at different stages of these projects life- cycle; from engineering and construction to closeout and disputes.
Kirkkuk Cement Factory Power Plant
https://proctal.com/power-generation/
This proposal seeks to develop a wireless WIM+NDE system as a solution to the premature transportation infrastructure safety problem, for the first time ever, in a two-fold approach: control of overloaded trucks and safety assessment/monitoring of transportation infrastructure. The system contains individual wireless sensing nodes that integrate state-of-the-art shear strain sensors suitable for concrete bridge components, and ultrasonic nondestructive evaluation (NDE) devices suitable for steel components.
NEXT-GENERATION WIRELESS BRIDGE WEIGH-IN-MOTION (WIM) SYSTEM INTEGRATED WITH NONDESTRUCTIVE EVALUATION (NDE) CAPABILITY FOR TRANSPORTATION INFRASTRUCTURE SAFETY
http://nctspm.gatech.edu/pi/next-generation-wireless-bridge-weigh-motion-wim-system-integrated-nondestructive-evaluation-nde
Social Services
Workshops, Inc.
https://www.linkedin.com/company/workshopsempowermentinc
https://media-exp1.licdn.com/dms/image/C4D0BAQGMQEWGccdA1Q/company-logo_100_100/0/1610119873697?e=1655942400&v=beta&t=cJnNe1tz1f3seir952r3sv6e352KZlkZbCMCfWlrfbQ
Volunteer for Assistance
Social Services
YouTube
https://www.linkedin.com/company/youtube
The channel provides a step by step procedure to investigate structures under Dynamic/Impact Loading Scenarios with more than 40K views. 
https://www.youtube.com/channel/UCMvJX7VH8KkeJwSmVbBlkmw
https://media-exp1.licdn.com/dms/image/C4D0BAQEfoRsyU4yUzg/company-logo_100_100/0/1631053379295?e=1655942400&v=beta&t=RnZ24gqDbifNCWylNL6b8fPlzF7Rvrkw4M--XYcf448
Created YouTube Channel to teach LS-Dyna applications in Civil Engineering
Science and Technology
Whioce Publishing
https://www.linkedin.com/company/whioce-publishing-pte-ltd-
https://media-exp1.licdn.com/dms/image/C510BAQHcNMNPk3qahA/company-logo_100_100/0/1519910942514?e=1655942400&v=beta&t=R3I_jasGVF_mwjK4LZxNqBKZ7Ht2dvkHEHN6DkMeh_g
Editor Member
Science and Technology
MDPI
https://www.linkedin.com/company/mdpi
https://media-exp1.licdn.com/dms/image/C4D0BAQEjhtG4qHq4bg/company-logo_100_100/0/1641815937490?e=1655942400&v=beta&t=ugI6p9GXcLvyC4hiyUDPhO9A_NAb5BBxNowDmhoxDJo
Reviewer
ASNT (The American Society for Nondestructive Testing)
https://www.linkedin.com/company/asntinfo
https://media-exp1.licdn.com/dms/image/C510BAQGg7CQb5tT-0Q/company-logo_100_100/0/1519879033414?e=1655942400&v=beta&t=ccBSBxxOvpT0SDNVKad4NRNcrUW7BhP3Kl5KKJ85Ws4
Reviewer
Science and Technology
Elsevier
https://www.linkedin.com/company/elsevier
https://media-exp1.licdn.com/dms/image/C4D0BAQFBLyBPRApt9A/company-logo_100_100/0/1647457162833?e=1655942400&v=beta&t=keNjpTcjl3D8z3Ix1Q1O4Nd7SwC6DYmiEpHKNXENujM
Reviewer
Science and Technology
Transportation Research Board: National Academies of Sciences, Engineering, and Medicine
https://www.linkedin.com/company/transportation-research-board-of-the-national-academies
https://media-exp1.licdn.com/dms/image/C4E0BAQHYS5UqfftKCQ/company-logo_100_100/0/1519888114622?e=1655942400&v=beta&t=tHcTc8ZaKHQ0LkWCSzFdfqwa50AaFEVLExaFTRYYppc
Review Panel
Science and Technology
American Society of Civil Engineers
https://www.linkedin.com/company/americansocietyofcivilengineers
Editorial Board Member at the Natural Hazard Review Journal
https://media-exp1.licdn.com/dms/image/C560BAQH1AMGXzrY4iQ/company-logo_100_100/0/1519855912111?e=1655942400&v=beta&t=4q2Qo0BoMApOuD3SsLbgTbIaP86qVxdAc5tS-BsDDbM
E.C. Editorial Board Member
Texas Board of Professional Engineers
engineers.texas.gov
129925
Professional Engineer (PE)
https://engineers.texas.gov/roster
Commonwealth of Kentucky
33475
Professional Engineer (PE)
Nevada Board of Engineers and Land Surveyors
www.linkedin.com
028458
Structural Engineer (SE)
https://www.linkedin.com/company/nevada-state-board-of-professional-engineers-and-land-surveyors/
https://www.linkedin.com/in/daniel-fisher-08b06851
Rockingham, NC
Daniel Fisher
Principal Engineer at SC Solutions
https://www.linkedin.com/in/samysaadahmed
Gardena, CA
Samy Saad
Senior Structural Engineer at AECOM
https://www.linkedin.com/in/vinayaksachidanandam
San Francisco Bay Area
Vinayak Sachidanandam
Nuclear Industry | Space Industry | Transportation
https://eg.linkedin.com/in/%D9%85-%D8%B3%D9%84%D9%8A%D9%85%D8%A7%D9%86-%D8%A7%D9%84%D8%B9%D8%B7%D8%A7%D8%B1%D9%8A-499a94224
Cairo
م. سليمان العطاري
كبير مهندسين في هايديليكو
https://www.linkedin.com/in/reyhanehnavabzadeh
Sacramento, CA
Reyhaneh Navabzadeh, PhD
Engineer II at SC Solutions
https://www.linkedin.com/in/melissa-hennessy-30348058
Boise, ID
Melissa Hennessy
--
https://eg.linkedin.com/in/nahla-mohamed-4611111b2
Alexandria, Egypt
NAHLA Mohamed
Human Resources Specialist at Engineering Consultants Group S.A.
https://www.linkedin.com/in/lynn-chelette-a5868516b
Greater Alexandria, Louisiana
lynn chelette
Engineer Technician 7 at La DOTD
https://www.linkedin.com/in/mahantesh-s-hiremath
San Francisco Bay Area
Mahantesh Hiremath
Vice President, SC Solutions
https://eg.linkedin.com/in/ahmedmoustafa00
Giza
Ahmed Moustafa Aboelela
BSc., PRMG, CLAC, PCT, A.M.ASCE, MCIArb, CICCM, LLM, MBA (Cand.). | Contracts Engineer Team Leader at Elsewedy Electric T&D | Calibers Co-Founder & COO | We Enjoy Being a Part of Your Success Story.
https://www.linkedin.com/in/abdul-wahid-mangi-668623118
Houston, TX
Abdul Wahid Mangi
Ph.D. Scholar
https://www.linkedin.com/in/aaron-marga-pe-mba-50b05693
Pittsburgh, PA
Aaron Marga, PE, MBA
Bridge Design Lead
https://ae.linkedin.com/in/abdelrahman-alsallamin-985ab017a
United Arab Emirates
Abdelrahman Alsallamin
MSc. in Civil Engineering, Lab Engineer at UAE University 
Incharge of Concrete Technology & Soil Mechanics Laboratories
https://www.linkedin.com/in/harshnandan
San Francisco Bay Area
Harsh Nandan
Software Engineering
https://www.linkedin.com/in/jeremy-dasher-4923b338
Pueblo, CO
Jeremy Dasher
Principal Investigator I at Transportation Technology Center, Inc
https://in.linkedin.com/in/anusha-suryanarayanan-pe-10118762
Pune
Anusha Suryanarayanan, PE
ISB AMPI '23 | Ex- WSP
https://www.linkedin.com/in/amir-ardalan-mosavi-ph-d-p-e-tx-ca-mi-ab152710
Greater Houston
Amir Ardalan Mosavi, Ph.D., P.E (TX, CA, MI)
Senior Engineer at Arup
https://www.linkedin.com/in/abmabdullah
Little Rock, AR
ABM Abdullah, PhD, PE
Senior Structures Engineer at Arkansas Department of Transportation
American Society of Civil Engineers (ASCE)
https://media-exp1.licdn.com/dms/image/C4D07AQHuIwktEFTIkw/group-logo_image-shrink_200x200/0/1631374864806?e=1647691200&v=beta&t=6LNiud4lu6jA4jVEwEO7JFCYt8OCYD2EIwxlIcOxxtU
https://www.linkedin.com/groups/143956
Florida Structural Engineers Association - FSEA
https://media-exp1.licdn.com/dms/image/C5607AQHld7mlf5NXHA/group-logo_image-shrink_92x92/0/1631000658198?e=1647691200&v=beta&t=clYAlEds1OWsNdWlMrH0B4gtFxRSE2u-1qZCUcJI6G0
https://www.linkedin.com/groups/3038388