Alkali-Activated Natural Pozzolan Concrete as New Construction Material

In the near future, geopolymers or alkali-activated cementitious materials will be used as new high-performance construction materials of low environmental impact with a reasonable cost. This material is a good candidate to partially replace ordinary portland cement (OPC) in concrete as a major construction material that plays an outstanding role in the construction industry of different structures. Geopolymer materials are inorganic polymers based on alumina and silica units; they are synthesized from a wide range of dehydroxylated alumina-silicate powders condensed with alkaline silicate in a highly alkaline environment. Geopolymeric materials can be produced from a wide range of alumina-silica, including natural products--such as natural pozzolan and metakaolin--or coproducts--such as fly ash (coal and lignite), oil fuel ash, blast furnace or steel slag, and silica fume--and provide a route toward sustainable development. Using lesser amounts of calcium-based raw materials, lower manufacturing temperature, and lower amounts of fuel result in reduced carbon emissions for geopolymer cement manufacture up to 22 to 72% in comparison with portland cement. A study has been done by the authors to investigate the intrinsic nature of different types of Iranian natural pozzolans to determine the activators and methods that could be used to produce a geopolymer concrete based on alkali-activated natural pozzolan (AANP) and optimize mixture design. The mechanical behavior and durability of these types of geopolymer concrete were investigated and compared with normal OPC concrete mixtures cast by the authors and also reported in the literature. This paper summarizes the main conclusions of the research regarding pozzolanic activity, activator properties, engineering and durability properties, applications and evaluation of carbon footprint, and cost for AANP concrete.

Use of a Neural Network to Predict Strength and Optimum Compositions of Natural Alumina-Silica-Based Geopolymers

In order to predict compressive strength of geopolymers prepared from alumina-silica natural products, based on the effect of Al 2 O 3 /SiO 2, Na 2 O/Al 2 O 3, Na 2 O/H 2 O, and Na/[Na+K], more than 50 pieces of data were gathered from the literature. The data was utilized to train and test a multilayer artificial neural network (ANN). Therefore a multilayer feedforward network was designed with chemical compositions of alumina silicate and alkali activators as inputs and compressive strength as output. In this study, a feedforward network with various numbers of hidden layers and neurons were tested to select the optimum network architecture. The developed three-layer neural network simulator model used the feedforward back propagation architecture, demonstrated its ability in training the given input/output patterns. The cross-validation data was used to show the validity and high prediction accuracy of the network. This leads to the optimum chemical composition and the best paste can be made from activated alumina-silica natural products using alkaline hydroxide, and alkaline silicate. The research results are in agreement with mechanism of geopolymerization.


Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)MT.1943-5533.0000829

The effect of changing the built environment on physical activity: a quantitative review of the risk of bias in natural experiments.

BACKGROUND:
Evidence regarding the association of the built environment with physical activity is influencing policy recommendations that advocate changing the built environment to increase population-level physical activity. However, to date there has been no rigorous appraisal of the quality of the evidence on the effects of changing the built environment. The aim of this review was to conduct a thorough quantitative appraisal of the risk of bias present in those natural experiments with the strongest experimental designs for assessing the causal effects of the built environment on physical activity.

METHODS:
Eligible studies had to evaluate the effects of changing the built environment on physical activity, include at least one measurement before and one measurement of physical activity after changes in the environment, and have at least one intervention site and non-intervention comparison site. Given the large number of systematic reviews in this area, studies were identified from three exemplar systematic reviews; these were published in the past five years and were selected to provide a range of different built environment interventions. The risk of bias in these studies was analysed using the Cochrane Risk of Bias Assessment Tool: for Non-Randomized Studies of Interventions (ACROBAT-NRSI).

RESULTS:
Twelve eligible natural experiments were identified. Risk of bias assessments were conducted for each physical activity outcome from all studies, resulting in a total of fifteen outcomes being analysed. Intervention sites included parks, urban greenways/trails, bicycle lanes, paths, vacant lots, and a senior citizen's centre. All outcomes had an overall critical (n = 12) or serious (n = 3) risk of bias. Domains with the highest risk of bias were confounding (due to inadequate control sites and poor control of confounding variables), measurement of outcomes, and selection of the reported result.

CONCLUSIONS:
The present review focused on the strongest natural experiments conducted to date. Given this, the failure of existing studies to adequately control for potential sources of bias highlights the need for more rigorous research to underpin policy recommendations for changing the built environment to increase physical activity. Suggestions are proposed for how future natural experiments in this area can be improved.