Thursday, May 10, 2012

University of Texas at Austin research awards promote algae fuel production, coastal security

University of Texas at Austin research awards promote algae fuel production, coastal security [ Back to EurekAlert! ] Public release date: 9-May-2012
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Contact: Tim Green
timgreen@mail.utexas.edu
512-475-6596
University of Texas at Austin

AUSTIN, Texas Two University of Texas at Austin faculty members have won Moncrief Grand Challenge Faculty Awards to develop computer models for algae-based fuel production and improve the security of coastal waters.

Venkat Raman, associate professor in the Department of Aerospace Engineering and Engineering Mechanics, and Yen-Hsi "Richard" Tsai, associate professor in the Department of Mathematics, are eligible to receive up to $75,000 during the 2012-2013 academic year to conduct their research at the university's Institute for Computational Engineering and Sciences (ICES).

The program is funded through the private donations of oilman and philanthropist W. A. "Tex" Moncrief of Fort Worth and an anonymous donor for work performed in ICES on grand challenges in computational engineering and sciences that affect the competitiveness and international standing of the United States.

Raman will work on computational modeling of photobioreactors for algae-based fuel production. A photobioreactor is a vessel in which sunlight promotes biochemical reactions in algae. Algae growth is highly sensitive to the light exposure, which is directly controlled by the turbulent flow inside the reactor. Large-scale turbulent mixing not only changes light attenuation through the growth medium, it also affects the exposure time of the algae cells to different light conditions. Understanding these fundamental interactions will also enable the design of large-scale photobioreactors.

Tsai will work on improving the security and effectiveness of patrolling the coasts of the United States, a concern related to national security. His research will target the development of patrol path planning strategies and the corresponding mathematical and computational models.

The U.S. Coast Guard faces ever-more-demanding requirements in patrolling coastal areas and could benefit from novel approaches.

Grand challenges are problems that must be addressed to achieve a sustainable, economically robust and politically stable future. These involve using computational methods to study such topics as cardiovascular engineering, water sustainability and weather. Other areas of grand challenges include carbon sequestration, drug design and delivery, advanced materials, rising seas modeling, national security, nano-science and engineering, and computational medicine and biomedicine.

During the past four years the Moncrief Grand Challenge Awards Program has provided more than $1 million in funding for University of Texas at Austin faculty members to pursue research in computational science and engineering.

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AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.


University of Texas at Austin research awards promote algae fuel production, coastal security [ Back to EurekAlert! ] Public release date: 9-May-2012
[ | E-mail | Share Share ]

Contact: Tim Green
timgreen@mail.utexas.edu
512-475-6596
University of Texas at Austin

AUSTIN, Texas Two University of Texas at Austin faculty members have won Moncrief Grand Challenge Faculty Awards to develop computer models for algae-based fuel production and improve the security of coastal waters.

Venkat Raman, associate professor in the Department of Aerospace Engineering and Engineering Mechanics, and Yen-Hsi "Richard" Tsai, associate professor in the Department of Mathematics, are eligible to receive up to $75,000 during the 2012-2013 academic year to conduct their research at the university's Institute for Computational Engineering and Sciences (ICES).

The program is funded through the private donations of oilman and philanthropist W. A. "Tex" Moncrief of Fort Worth and an anonymous donor for work performed in ICES on grand challenges in computational engineering and sciences that affect the competitiveness and international standing of the United States.

Raman will work on computational modeling of photobioreactors for algae-based fuel production. A photobioreactor is a vessel in which sunlight promotes biochemical reactions in algae. Algae growth is highly sensitive to the light exposure, which is directly controlled by the turbulent flow inside the reactor. Large-scale turbulent mixing not only changes light attenuation through the growth medium, it also affects the exposure time of the algae cells to different light conditions. Understanding these fundamental interactions will also enable the design of large-scale photobioreactors.

Tsai will work on improving the security and effectiveness of patrolling the coasts of the United States, a concern related to national security. His research will target the development of patrol path planning strategies and the corresponding mathematical and computational models.

The U.S. Coast Guard faces ever-more-demanding requirements in patrolling coastal areas and could benefit from novel approaches.

Grand challenges are problems that must be addressed to achieve a sustainable, economically robust and politically stable future. These involve using computational methods to study such topics as cardiovascular engineering, water sustainability and weather. Other areas of grand challenges include carbon sequestration, drug design and delivery, advanced materials, rising seas modeling, national security, nano-science and engineering, and computational medicine and biomedicine.

During the past four years the Moncrief Grand Challenge Awards Program has provided more than $1 million in funding for University of Texas at Austin faculty members to pursue research in computational science and engineering.

###



[ Back to EurekAlert! ] [ | E-mail | Share Share ]

?


AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.


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