Lime softening has been commonly used for decades for hardness removal in water treatment. Many methods are used for controlling lime feed to a water treatment system. Concentrations in influent to or effluent from a water softener are most often determined manually by physical measurements, though they can also be automatically measured by various devices. Based on influent concentrations, hand calculations can be made for determination of the required chemical feed. Alternatively, required lime dosage can be estimated and then adjusted until the desired effluent quality is attained. This type of iterative method requires special attention and multiple adjustments under circumstances where raw water quality fluctuates. The purpose of this study is to develop a spreadsheet that can work with existing equipment to improve on these existing methods for lime softening. A spreadsheet, utilizing the Bar Graph Method (Gullicks) could perform the necessary calculations for determining chemical feed based on user inputs. On-line measuring devices (hardness, alkalinity, pH, temperature and conductivity) would determine influent water quality to softening basins on a continuous basis. Supplemented with periodic analyses of Na+, SO42- and Cl- and small adjustments for conductivity variation, this software and hardware would then work together to automatically adjust chemical feed on a more continuous basis, providing a more consistent treated effluent, and a more efficient use of chemicals.
","abstract_html":"<p>Lime softening has been commonly used for decades for hardness removal in water treatment. Many methods are used for controlling lime feed to a water treatment system. Concentrations in influent to or effluent from a water softener are most often determined manually by physical measurements, though they can also be automatically measured by various devices. Based on influent concentrations, hand calculations can be made for determination of the required chemical feed. Alternatively, required lime dosage can be estimated and then adjusted until the desired effluent quality is attained. This type of iterative method requires special attention and multiple adjustments under circumstances where raw water quality fluctuates. The purpose of this study is to develop a spreadsheet that can work with existing equipment to improve on these existing methods for lime softening. A spreadsheet, utilizing the Bar Graph Method (Gullicks) could perform the necessary calculations for determining chemical feed based on user inputs. On-line measuring devices (hardness, alkalinity, pH, temperature and conductivity) would determine influent water quality to softening basins on a continuous basis. Supplemented with periodic analyses of Na+, SO42- and Cl- and small adjustments for conductivity variation, this software and hardware would then work together to automatically adjust chemical feed on a more continuous basis, providing a more consistent treated effluent, and a more efficient use of chemicals.</p>","abstract_has_math":false,"creators":["Norberg, James"],"institution":null,"degree_name":"Master of Science (MS)","degree_level":"Thesis","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Harvey Gullicks"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-01-01T08:00:00Z","date_published":"2012-01-01T08:00:00Z","updated_at":"2026-07-24T03:26:17Z","subjects":["Automation, Bar Graph, Chemistry, Lime Softening, Spreadsheet, Water"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.und.edu/theses/1308","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Harvey Gullicks"]},{"key":"dc:creator","label":"Author","values":["Norberg, James"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Automation, Bar Graph, Chemistry, Lime Softening, Spreadsheet, Water"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.und.edu/theses/1308"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Lime softening has been commonly used for decades for hardness removal in water treatment. Many methods are used for controlling lime feed to a water treatment system. Concentrations in influent to or effluent from a water softener are most often determined manually by physical measurements, though they can also be automatically measured by various devices. Based on influent concentrations, hand calculations can be made for determination of the required chemical feed. Alternatively, required lime dosage can be estimated and then adjusted until the desired effluent quality is attained. This type of iterative method requires special attention and multiple adjustments under circumstances where raw water quality fluctuates. The purpose of this study is to develop a spreadsheet that can work with existing equipment to improve on these existing methods for lime softening. A spreadsheet, utilizing the Bar Graph Method (Gullicks) could perform the necessary calculations for determining chemical feed based on user inputs. On-line measuring devices (hardness, alkalinity, pH, temperature and conductivity) would determine influent water quality to softening basins on a continuous basis. Supplemented with periodic analyses of Na+, SO42- and Cl- and small adjustments for conductivity variation, this software and hardware would then work together to automatically adjust chemical feed on a more continuous basis, providing a more consistent treated effluent, and a more efficient use of chemicals.
"]},{"key":"dc:title","label":"Title","values":["Development Of A Spreadsheet For Bar Graph Softening"]}]}],"canonical_facts":{"dc:contributor":["Harvey Gullicks"],"dc:creator":["Norberg, James"],"dc:description.abstract":["Lime softening has been commonly used for decades for hardness removal in water treatment. Many methods are used for controlling lime feed to a water treatment system. Concentrations in influent to or effluent from a water softener are most often determined manually by physical measurements, though they can also be automatically measured by various devices. Based on influent concentrations, hand calculations can be made for determination of the required chemical feed. Alternatively, required lime dosage can be estimated and then adjusted until the desired effluent quality is attained. This type of iterative method requires special attention and multiple adjustments under circumstances where raw water quality fluctuates. The purpose of this study is to develop a spreadsheet that can work with existing equipment to improve on these existing methods for lime softening. A spreadsheet, utilizing the Bar Graph Method (Gullicks) could perform the necessary calculations for determining chemical feed based on user inputs. On-line measuring devices (hardness, alkalinity, pH, temperature and conductivity) would determine influent water quality to softening basins on a continuous basis. Supplemented with periodic analyses of Na+, SO42- and Cl- and small adjustments for conductivity variation, this software and hardware would then work together to automatically adjust chemical feed on a more continuous basis, providing a more consistent treated effluent, and a more efficient use of chemicals.
"],"dc:identifier":["https://commons.und.edu/theses/1308"],"dc:subject":["Automation, Bar Graph, Chemistry, Lime Softening, Spreadsheet, Water"],"dc:title":["Development Of A Spreadsheet For Bar Graph Softening"],"thesis:degree_discipline":["Civil Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T03:26:17Z"}