MARYAM SAKHAEIFAR

Texas A&M University

 

Research Experience and Interests

Mechanics of Construction Materials

Microstructural Characterization of Asphaltic Material

Advanced modeling of asphalt concrete characterization.

Developing (Artificial Neural Network and Genetic Programming) analysis tools for pavement systems.

Demonstrated knowledge in Mechanistic-Empirical Pavement Design Guide.

Sustainable Civil Engineering Materials

Laboratory testing.

Testing and modeling pavement performance characterization.

Nondestructive evaluation of pavement systems.

Tire-pavement noise analysis.

Pavement design, rehabilitation, construction, preservation and modeling techniques.

Anti-seismic design of soil, industrial steel and reinforced concrete structures.

Infrastructure Management

Pavement management and rehabilitation.

Pavement preservation and life cycle cost analysis.

Network level automated pavement condition survey.


Teaching Experience

Texas A&M University, College Station, TX

CVEN 306: Materials Engineering for Civil Engineers

CVEN 342: Materials of Construction

CVEN 615: Structural Design of Pavements

CVEN 689: Mechanics of Viscoelastic Material (F2017)

CVEN 681: Seminar

Auburn University, Auburn, AL

CIVIL7840: Pavement Management and Rehabilitation

National Center for Asphalt Technology, Auburn, AL

Asphalt Technology Course

 North Carolina State University, Raleigh, NC

CE332: Materials of Construction (TA & Lab Instructor)

CE759: Inelastic Behavior of Construction Material (Mentored Teaching Assistant)


Software Development

ANNACAP (renamed to "LTPP*"): Artificial Neural Network for Asphalt Concrete Dynamic Modulus Prediction   

North Carolina State University, Aug. 2010

Windows based executable software, programmed with LabVIEW codes,                                - A general-purpose package for predicting the pavement response including a graphical user interface for preprocessing, predicting, postprocessing and input/output quality control checks,                                                                                                                                            

The software was submitted to Federal Highway Administration (FHWA) for populating the Long Term Pavement Performance (LTPP) database with dynamic modulus values.

IRLab: Impact Resonance Laboratory Test Programmed with LabVIEW                       

North Carolina State University, Apr. 2007

A signal processing program including a graphical user interface

A quality control/quality assurance (QC/QA) tool to measure the dynamic modulus of hot mix asphalt (HMA) production rapidly.

Used for establishing a prototype to characterize the pavement response in an impact resonance (IR) test; prepared for Federal Highway Administration's (FHWA) task order.