As large countries such as China begin to industrialize and concerns about global warming continue to grow, there is an increasing need for more environmentally friendly building materials. One promising material known as a geopolymer can be used as a portland cement replacement and in this capacity emits around 67% less carbon dioxide. In addition to potentially reducing carbon emissions, geopolymers can be synthesized with many industrial waste products such as fly ash.
Although the benefits of geopolymers are substantial, there are a few difficulties with designing geopolymer mixes which have hindered widespread commercialization of the material. One such difficulty is the high variability of the materials used for their synthesis. In addition to this, interrelationships between mix design variables and how these interrelationships impact the set behavior and compressive strength are not well understood. A third complicating factor with designing geopolymer mixes is that the role of calcium in these systems is not well understood.
In order to overcome these barriers, this study developed predictive optimization models through the use of genetic programming with experimentally collected set times and compressive strengths of several geopolymer paste mixes. The developed set behavior models were shown to predict the correct set behavior from the mix design over 85% of the time. The strength optimization model was shown to be capable of predicting compressive strengths of geopolymer pastes from their mix design to within about 1 ksi of their actual strength. In addition to this the optimization models give valuable insight into the key factors influencing strength development as well as the key factors responsible for flash set and long set behaviors in geopolymer pastes.
A method for designing geopolymer paste mixes was developed from the generated optimization models. This design method provides an invaluable tool for use in future geopolymer research as well as commercial development of geopolymer products.
","abstract_html":"<p>As large countries such as China begin to industrialize and concerns about global warming continue to grow, there is an increasing need for more environmentally friendly building materials. One promising material known as a geopolymer can be used as a portland cement replacement and in this capacity emits around 67% less carbon dioxide. In addition to potentially reducing carbon emissions, geopolymers can be synthesized with many industrial waste products such as fly ash.</p><p>Although the benefits of geopolymers are substantial, there are a few difficulties with designing geopolymer mixes which have hindered widespread commercialization of the material. One such difficulty is the high variability of the materials used for their synthesis. In addition to this, interrelationships between mix design variables and how these interrelationships impact the set behavior and compressive strength are not well understood. A third complicating factor with designing geopolymer mixes is that the role of calcium in these systems is not well understood.</p><p>In order to overcome these barriers, this study developed predictive optimization models through the use of genetic programming with experimentally collected set times and compressive strengths of several geopolymer paste mixes. The developed set behavior models were shown to predict the correct set behavior from the mix design over 85% of the time. The strength optimization model was shown to be capable of predicting compressive strengths of geopolymer pastes from their mix design to within about 1 ksi of their actual strength. In addition to this the optimization models give valuable insight into the key factors influencing strength development as well as the key factors responsible for flash set and long set behaviors in geopolymer pastes.</p><p>A method for designing geopolymer paste mixes was developed from the generated optimization models. This design method provides an invaluable tool for use in future geopolymer research as well as commercial development of geopolymer products.</p>","abstract_has_math":false,"creators":["Fillenwarth, Brian Albert"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Mechanical Engineering and Materials Science","degree_department":null,"school":null,"contributors":["Shankar M.L. Sastry"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-04-25T07:00:00Z","date_published":"2013-04-25T07:00:00Z","updated_at":"2026-07-24T06:13:49Z","subjects":["compressive strength","fly ash","geopolymer paste","mix design tables","predictive optimization model","set time","Mechanical Engineering"],"languages":["English (en)"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.7936/K7125QQ7"],"render_values":[{"text":"https://doi.org/10.7936/K7125QQ7","href":"https://doi.org/10.7936/K7125QQ7","code":true}]}]},"links":{"outbound_url":"https://openscholarship.wustl.edu/etd/1096","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Shankar M.L. Sastry"]},{"key":"dc:creator","label":"Author","values":["Fillenwarth, Brian Albert"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2015-08-19T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering and Materials Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["compressive strength","fly ash","geopolymer paste","mix design tables","predictive optimization model","set time","Mechanical Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English (en)"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://openscholarship.wustl.edu/etd/1096"]},{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.7936/K7125QQ7"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["As large countries such as China begin to industrialize and concerns about global warming continue to grow, there is an increasing need for more environmentally friendly building materials. One promising material known as a geopolymer can be used as a portland cement replacement and in this capacity emits around 67% less carbon dioxide. In addition to potentially reducing carbon emissions, geopolymers can be synthesized with many industrial waste products such as fly ash.
Although the benefits of geopolymers are substantial, there are a few difficulties with designing geopolymer mixes which have hindered widespread commercialization of the material. One such difficulty is the high variability of the materials used for their synthesis. In addition to this, interrelationships between mix design variables and how these interrelationships impact the set behavior and compressive strength are not well understood. A third complicating factor with designing geopolymer mixes is that the role of calcium in these systems is not well understood.
In order to overcome these barriers, this study developed predictive optimization models through the use of genetic programming with experimentally collected set times and compressive strengths of several geopolymer paste mixes. The developed set behavior models were shown to predict the correct set behavior from the mix design over 85% of the time. The strength optimization model was shown to be capable of predicting compressive strengths of geopolymer pastes from their mix design to within about 1 ksi of their actual strength. In addition to this the optimization models give valuable insight into the key factors influencing strength development as well as the key factors responsible for flash set and long set behaviors in geopolymer pastes.
A method for designing geopolymer paste mixes was developed from the generated optimization models. This design method provides an invaluable tool for use in future geopolymer research as well as commercial development of geopolymer products.
"]},{"key":"dc:title","label":"Title","values":["Development of Optimization Models for the Set Behavior and Compressive Strength of Sodium Activated Geopolymer Pastes"]}]}],"canonical_facts":{"dc:contributor":["Shankar M.L. Sastry"],"dc:creator":["Fillenwarth, Brian Albert"],"dc:date.available":["2015-08-19T07:00:00Z"],"dc:description.abstract":["As large countries such as China begin to industrialize and concerns about global warming continue to grow, there is an increasing need for more environmentally friendly building materials. One promising material known as a geopolymer can be used as a portland cement replacement and in this capacity emits around 67% less carbon dioxide. In addition to potentially reducing carbon emissions, geopolymers can be synthesized with many industrial waste products such as fly ash.
Although the benefits of geopolymers are substantial, there are a few difficulties with designing geopolymer mixes which have hindered widespread commercialization of the material. One such difficulty is the high variability of the materials used for their synthesis. In addition to this, interrelationships between mix design variables and how these interrelationships impact the set behavior and compressive strength are not well understood. A third complicating factor with designing geopolymer mixes is that the role of calcium in these systems is not well understood.
In order to overcome these barriers, this study developed predictive optimization models through the use of genetic programming with experimentally collected set times and compressive strengths of several geopolymer paste mixes. The developed set behavior models were shown to predict the correct set behavior from the mix design over 85% of the time. The strength optimization model was shown to be capable of predicting compressive strengths of geopolymer pastes from their mix design to within about 1 ksi of their actual strength. In addition to this the optimization models give valuable insight into the key factors influencing strength development as well as the key factors responsible for flash set and long set behaviors in geopolymer pastes.
A method for designing geopolymer paste mixes was developed from the generated optimization models. This design method provides an invaluable tool for use in future geopolymer research as well as commercial development of geopolymer products.
"],"dc:identifier":["https://openscholarship.wustl.edu/etd/1096"],"dc:identifier.doi":["https://doi.org/10.7936/K7125QQ7"],"dc:language":["English (en)"],"dc:subject":["compressive strength","fly ash","geopolymer paste","mix design tables","predictive optimization model","set time","Mechanical Engineering"],"dc:title":["Development of Optimization Models for the Set Behavior and Compressive Strength of Sodium Activated Geopolymer Pastes"],"thesis:degree_discipline":["Mechanical Engineering and Materials Science"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T06:13:49Z"}