title: Characterizing the mechanical properties of fused deposition modelling natural fiber recycled polypropylene composites

authors: Milosevic, M.

abstract: The objective of this investigation was to characterize the performance of natural fiber reinforced polypropylene composites in fused deposition modelling (FDM). Composite filaments comprising of pre-consumer recycled polypropylene with varying contents of hemp or harakeke fibers were extruded from which tensile test specimens were made using FDM. Filament and test specimens were tensile tested and properties were compared with plain polypropylene samples; the ultimate tensile strength and Young’s modulus of reinforced filament increased by more than 50% and 143%, respectively, for both 30 wt % hemp or harakeke compared to polypropylene filament. However, the same degree of improvement was not seen with the FDM test specimens, with several compositions having properties lower than for unfilled polypropylene. SEM analysis of fracture surfaces revealed uniform fiber dispersion and reasonable fiber alignment, but porosity and fiber pull-out were also observed. Fiber reinforcement was found to give benefit regarding dimensional stability during extrusion and FDM, which is of major importance for its implementation in FDM. Recommendations for optimization of processing in order to enhance build quality and improve mechanical properties are provided.

text: Characterizing the mechanical properties of fused deposition modelling natural fiber recycled polypropylene composites The objective of this investigation was to characterize the performance of natural fiber reinforced polypropylene composites in fused deposition modelling (FDM). Composite filaments comprising of pre-consumer recycled polypropylene with varying contents of hemp or harakeke fibers were extruded from which tensile test specimens were made using FDM. Filament and test specimens were tensile tested and properties were compared with plain polypropylene samples; the ultimate tensile strength and Young’s modulus of reinforced filament increased by more than 50% and 143%, respectively, for both 30 wt % hemp or harakeke compared to polypropylene filament. However, the same degree of improvement was not seen with the FDM test specimens, with several compositions having properties lower than for unfilled polypropylene. SEM analysis of fracture surfaces revealed uniform fiber dispersion and reasonable fiber alignment, but porosity and fiber pull-out were also observed. Fiber reinforcement was found to give benefit regarding dimensional stability during extrusion and FDM, which is of major importance for its implementation in FDM. Recommendations for optimization of processing in order to enhance build quality and improve mechanical properties are provided.

year: 2017

title: Temporal moments of a tracer pulse in a perfectly parallel flow system

authors: Bardsley, W. Earl

subjects: stratified aquifier

abstract: Perfectly parallel groundwater transport models partition water flow into isolated one-dimensional stream tubes which maintain total spatial correlation of all properties in the direction of flow. The case is considered of the temporal moments of a conservative tracer pulse released simultaneously into N stream tubes with arbitrarily different advective–dispersive transport and steady flow speeds in each of the stream tubes. No assumptions are made about the form of the individual stream tube arrival-time distributions or about the nature of the between-stream tube variation of hydraulic conductivity and flow speeds. The tracer arrival-time distribution g(t,x) is an N-component finite-mixture distribution, with the mean and variance of each component distribution increasing in proportion to tracer travel distance x. By utilising moment relations of finite mixture distributions, it is shown (to r=4) that the rth central moment of g(t,x) is an rth order polynomial function of x or φ, where φ is mean arrival time. In particular, the variance of g(t,x) is a positive quadratic function of x or φ. This generalises the well-known quadratic variance increase for purely advective flow in parallel flow systems and allows a simple means of regression estimation of the large-distance coefficient of variation of g(t,x). The polynomial central moment relation extends to the purely advective transport case which arises as a large-distance limit of advective–dispersive transport in parallel flow models. The associated limit g(t,x) distributions are of N-modal form and maintain constant shapes independent of travel distance. The finite-mixture framework for moment evaluation is also a potentially useful device for forecasting g(t,x) distributions, which may include multimodal forms. A synthetic example illustrates g(t,x) forecasting using a mixture of normal distributions.

text: Temporal moments of a tracer pulse in a perfectly parallel flow system Perfectly parallel groundwater transport models partition water flow into isolated one-dimensional stream tubes which maintain total spatial correlation of all properties in the direction of flow. The case is considered of the temporal moments of a conservative tracer pulse released simultaneously into N stream tubes with arbitrarily different advective–dispersive transport and steady flow speeds in each of the stream tubes. No assumptions are made about the form of the individual stream tube arrival-time distributions or about the nature of the between-stream tube variation of hydraulic conductivity and flow speeds. The tracer arrival-time distribution g(t,x) is an N-component finite-mixture distribution, with the mean and variance of each component distribution increasing in proportion to tracer travel distance x. By utilising moment relations of finite mixture distributions, it is shown (to r=4) that the rth central moment of g(t,x) is an rth order polynomial function of x or φ, where φ is mean arrival time. In particular, the variance of g(t,x) is a positive quadratic function of x or φ. This generalises the well-known quadratic variance increase for purely advective flow in parallel flow systems and allows a simple means of regression estimation of the large-distance coefficient of variation of g(t,x). The polynomial central moment relation extends to the purely advective transport case which arises as a large-distance limit of advective–dispersive transport in parallel flow models. The associated limit g(t,x) distributions are of N-modal form and maintain constant shapes independent of travel distance. The finite-mixture framework for moment evaluation is also a potentially useful device for forecasting g(t,x) distributions, which may include multimodal forms. A synthetic example illustrates g(t,x) forecasting using a mixture of normal distributions.

year: 2003-06

title: He pakiriha

authors: Temara, Pou

subjects: Tikanga

abstract: Kua tae ki te wā hai kōrero i ētahi tikanga marae, ētahi tikanga kawa e kawa ana ki tā te mātanga titiro. Tērā ētahi tikanga e whakamahia ana e ngā kaumātua o nāianei e uru atu ana ki te pae o rorirori, ka mutu, e ai ki tā ngā kaumātua nei, ko te mutunga mai o te tika ā rātau i whakatau ai. Nā hei whakarāpopoto i te whakaaro whānui, i ētahi wā kāore ko te mea e tika ana ki ō tātau whakaaro te huarahi pai. Ko tā te tikanga he kimi i te huarahi e tika ana, kia kore ai e whara ngā whakaaro o te tangata. Ko te tikanga ehara i te mea i whakairotia ki te kōhatu, engari e taea ana te neke i ngā pae o te tikanga kia pai ai te whakahaere a te tangata i āna mahi, kia tau ai te rangimārie, kia mau tonu ai te mana o te tangata. E whakapae ana ahau e kūmea ana e ētahi kaumātua ētahi tikanga kia hāngai ki tā rātau i whakaaro ai kai te tika, kai te hē rānei. Mā ētahi tauira e mārama ai te kaipānui ki te kaupapa me te whakaaro o te kaituhi.

text: He pakiriha Kua tae ki te wā hai kōrero i ētahi tikanga marae, ētahi tikanga kawa e kawa ana ki tā te mātanga titiro. Tērā ētahi tikanga e whakamahia ana e ngā kaumātua o nāianei e uru atu ana ki te pae o rorirori, ka mutu, e ai ki tā ngā kaumātua nei, ko te mutunga mai o te tika ā rātau i whakatau ai. Nā hei whakarāpopoto i te whakaaro whānui, i ētahi wā kāore ko te mea e tika ana ki ō tātau whakaaro te huarahi pai. Ko tā te tikanga he kimi i te huarahi e tika ana, kia kore ai e whara ngā whakaaro o te tangata. Ko te tikanga ehara i te mea i whakairotia ki te kōhatu, engari e taea ana te neke i ngā pae o te tikanga kia pai ai te whakahaere a te tangata i āna mahi, kia tau ai te rangimārie, kia mau tonu ai te mana o te tangata. E whakapae ana ahau e kūmea ana e ētahi kaumātua ētahi tikanga kia hāngai ki tā rātau i whakaaro ai kai te tika, kai te hē rānei. Mā ētahi tauira e mārama ai te kaipānui ki te kaupapa me te whakaaro o te kaituhi.

year: 2017