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"Domain Area"

Date SubmittedNameInstitutionDomain AreaResearch Programme# Active MembersAllocation PeriodHours UsedPress Release
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2023-01-01Wood, NatashaUPBioinformaticsCBBI080562016-01-23 -- 2018-05-03503177The HIV Molecular Dynamics research group forms part of the Computational Biology division within the Department of Integrative Biomedical Sciences (IBMS) at the University of Cape Town. This small, but dynamic, group focussed on generating computer simulations of the HIV surface protein, which forms the first contact between the virus and the human CD4+ immune cells. This surface protein, Envelope, is covered with carbohydrates that are added by the human cell machinery during its formation. Since these carbohydrates are added by the host, they are not marked as foreign by the human immune system as would be the case for other infectious agents.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
The 300-word press release is targeted at a non-specialist audience who, although well-educated, must be assumed to be unfamiliar with the particular scientific domain.

"Domain Area"

Date SubmittedNameInstitutionDomain AreaResearch Programme# Active MembersAllocation PeriodHours UsedPress Release
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2023-01-01Wood, NatashaUPBioinformaticsCBBI080562016-01-23 -- 2018-05-03503177The HIV Molecular Dynamics research group forms part of the Computational Biology division within the Department of Integrative Biomedical Sciences (IBMS) at the University of Cape Town. This small, but dynamic, group focussed on generating computer simulations of the HIV surface protein, which forms the first contact between the virus and the human CD4+ immune cells. This surface protein, Envelope, is covered with carbohydrates that are added by the human cell machinery during its formation. Since these carbohydrates are added by the host, they are not marked as foreign by the human immune system as would be the case for other infectious agents.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
The 300-word press release is targeted at a non-specialist audience who, although well-educated, must be assumed to be unfamiliar with the particular scientific domain.

"Domain Area"

Date SubmittedNameInstitutionDomain AreaResearch Programme# Active MembersAllocation PeriodHours UsedPress Release
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2023-01-01Wood, NatashaUPBioinformaticsCBBI080562016-01-23 -- 2018-05-03503177The HIV Molecular Dynamics research group forms part of the Computational Biology division within the Department of Integrative Biomedical Sciences (IBMS) at the University of Cape Town. This small, but dynamic, group focussed on generating computer simulations of the HIV surface protein, which forms the first contact between the virus and the human CD4+ immune cells. This surface protein, Envelope, is covered with carbohydrates that are added by the human cell machinery during its formation. Since these carbohydrates are added by the host, they are not marked as foreign by the human immune system as would be the case for other infectious agents.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
The 300-word press release is targeted at a non-specialist audience who, although well-educated, must be assumed to be unfamiliar with the particular scientific domain.

"Domain Area"

Date SubmittedNameInstitutionDomain AreaResearch Programme# Active MembersAllocation PeriodHours UsedPress Release
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2023-01-01Wood, NatashaUPBioinformaticsCBBI080562016-01-23 -- 2018-05-03503177The HIV Molecular Dynamics research group forms part of the Computational Biology division within the Department of Integrative Biomedical Sciences (IBMS) at the University of Cape Town. This small, but dynamic, group focussed on generating computer simulations of the HIV surface protein, which forms the first contact between the virus and the human CD4+ immune cells. This surface protein, Envelope, is covered with carbohydrates that are added by the human cell machinery during its formation. Since these carbohydrates are added by the host, they are not marked as foreign by the human immune system as would be the case for other infectious agents.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
The 300-word press release is targeted at a non-specialist audience who, although well-educated, must be assumed to be unfamiliar with the particular scientific domain.

"Domain Area"

Date SubmittedNameInstitutionDomain AreaResearch Programme# Active MembersAllocation PeriodHours UsedPress Release
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2023-01-01Wood, NatashaUPBioinformaticsCBBI080562016-01-23 -- 2018-05-03503177The HIV Molecular Dynamics research group forms part of the Computational Biology division within the Department of Integrative Biomedical Sciences (IBMS) at the University of Cape Town. This small, but dynamic, group focussed on generating computer simulations of the HIV surface protein, which forms the first contact between the virus and the human CD4+ immune cells. This surface protein, Envelope, is covered with carbohydrates that are added by the human cell machinery during its formation. Since these carbohydrates are added by the host, they are not marked as foreign by the human immune system as would be the case for other infectious agents.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
The 300-word press release is targeted at a non-specialist audience who, although well-educated, must be assumed to be unfamiliar with the particular scientific domain.

"Domain Area"

Date SubmittedNameInstitutionDomain AreaResearch Programme# Active MembersAllocation PeriodHours UsedPress Release
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2023-01-01Wood, NatashaUPBioinformaticsCBBI080562016-01-23 -- 2018-05-03503177The HIV Molecular Dynamics research group forms part of the Computational Biology division within the Department of Integrative Biomedical Sciences (IBMS) at the University of Cape Town. This small, but dynamic, group focussed on generating computer simulations of the HIV surface protein, which forms the first contact between the virus and the human CD4+ immune cells. This surface protein, Envelope, is covered with carbohydrates that are added by the human cell machinery during its formation. Since these carbohydrates are added by the host, they are not marked as foreign by the human immune system as would be the case for other infectious agents.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
The 300-word press release is targeted at a non-specialist audience who, although well-educated, must be assumed to be unfamiliar with the particular scientific domain.

"Domain Area"

Date SubmittedNameInstitutionDomain AreaResearch Programme# Active MembersAllocation PeriodHours UsedPress Release
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2023-01-01Wood, NatashaUPBioinformaticsCBBI080562016-01-23 -- 2018-05-03503177The HIV Molecular Dynamics research group forms part of the Computational Biology division within the Department of Integrative Biomedical Sciences (IBMS) at the University of Cape Town. This small, but dynamic, group focussed on generating computer simulations of the HIV surface protein, which forms the first contact between the virus and the human CD4+ immune cells. This surface protein, Envelope, is covered with carbohydrates that are added by the human cell machinery during its formation. Since these carbohydrates are added by the host, they are not marked as foreign by the human immune system as would be the case for other infectious agents.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
The 300-word press release is targeted at a non-specialist audience who, although well-educated, must be assumed to be unfamiliar with the particular scientific domain.

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"Domain Area"

Date SubmittedNameInstitutionDomain AreaResearch Programme# Active MembersAllocation PeriodHours UsedPress Release
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2023-01-01Wood, NatashaUPBioinformaticsCBBI080562016-01-23 -- 2018-05-03503177The HIV Molecular Dynamics research group forms part of the Computational Biology division within the Department of Integrative Biomedical Sciences (IBMS) at the University of Cape Town. This small, but dynamic, group focussed on generating computer simulations of the HIV surface protein, which forms the first contact between the virus and the human CD4+ immune cells. This surface protein, Envelope, is covered with carbohydrates that are added by the human cell machinery during its formation. Since these carbohydrates are added by the host, they are not marked as foreign by the human immune system as would be the case for other infectious agents.
2023-01-01Maphanga, ReginaUL
Computational Chemistry
MATS091942016-07-28 -- 2018-05-0596232The group is called Advanced Mathematical Modelling based at Modelling and Digital Science unit of CSIR and uses multiscale methods to develop novel energy storage materials with desired properties and enhanced properties for existing materials. The envisaged outcome of this project is to develop energy storage materials models with improved performance and consistency, which will be cheaper and environmentally benign. The ever-increasing global energy needs and depleting fossil-fuel resources demand the pursuit of sustainable energy alternatives, including renewable sources to replace carbon intensive energy sources. Sustainable and renewable energy is considered to be the most effective way to minimize CO2 emissions. Hence, finding sustainable energy storage technologies is vital for optimally harnessing the renewable energy. Computational methodologies are very effective in predicting material-structure-property correlations. In this project simulation methods and models based on parallel computing are developed to probe battery materials properties. Centre for High Performance Computing (CHPC) resources are used to develop these parallel methods and algorithms for large and complex material models. Thus, CHPC resources provide a platform to simulate the evolution of material properties at a wide range of external conditions that are not accessible experimentally and fast track acquisition of results. The major of aim of this project is to create a predictive, reliable and robust set of models of materials for energy storage across the materials modelling length scale, leading to integrated multi-scale capability.
2024-01-01Chinyoka, TiriUWCCFDMECH094352016-10-10 -- 2018-05-052660878The research group's focus is centered on the complex flow of equally complex fluids and their commercial and industrial applications. Examples of completed projects include flows around aircraft landing gears in the modelling of noise reduction as well as complex flows of polymeric fluids generally as obtaining in the polymer, pharmaceutical and food industries. The scientific modelling of the complex flows of such complex fluids reduces to equally complicated systems of mathematical equations. These mathematical model equations cannot be solved by hand even for the most basic small scale applications. It is therefore necessary to develop scientific computing methods to simulate and solve these problems. This is where the group finds important linkages with the CHPC. The CHPC provides high speed computing facilities to assist in solving our mathematical equations. The computing speed is of fundamental importance as the relevant computations can take weeks or months on an average desktop computer. The collaboration with the CHPC has therefore enabled the group to resolve very complex problems with relative ease.
The 300-word press release is targeted at a non-specialist audience who, although well-educated, must be assumed to be unfamiliar with the particular scientific domain.
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