Genetic programming based formulation for fresh and hardened properties of self-compacting concrete containing pulverised fuel ash

Self-compacting concrete (SCC) flows into place and around obstructions under its own weight to fill the formwork completely and self-compact without any segregation and blocking. Elimination of the need for compaction leads to better quality concrete and substantial improvement of working conditions. This investigation aimed to show possible applicability of genetic programming (GP) to model and formulate the fresh and hardened properties of self-compacting concrete (SCC) containing pulverised fuel ash (PFA) based on experimental data. Twenty-six mixes were made with 0.38 to 0.72 water-to-binder ratio (W/B), 183–317 kg/m³ of cement content, 29–261 kg/m³ of PFA, and 0 to 1% of superplasticizer, by mass of powder. Parameters of SCC mixes modelled by genetic programming were the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength at 7, 28 and 90 days. GP is constructed of training and testing data using the experimental results obtained in this study. The results of genetic programming models are compared with experimental results and are found to be quite accurate. GP has showed a strong potential as a feasible tool for modelling the fresh properties and the compressive strength of SCC containing PFA and produced analytical prediction of these properties as a function as the mix ingredients. Results showed that the GP model thus developed is not only capable of accurately predicting the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength used in the training process, but it can also effectively predict the above properties for new mixes designed within the practical range with the variation of mix ingredients.

Effect of Mix Proportions on Rheological and Hardened Properties of Composite Cement Pastes

There is an increasing need to identify the effect of mix composition on the rheological properties of composite cement pastes using simple tests to determine the fluidity, the cohesion and other mechanical properties of grouting applications such as compressive strength. This paper reviews statistical models developed using a fractional factorial design which was carried out to model the influence of key parameters on properties affecting the performance of composite cement paste. Such responses of fluidity included mini-slump, flow time using Marsh cone and cohesion measured by Lombardi plate meter and unit weight, and compressive strength at 3 d, 7 d and 28 d. The models are valid for mixes with 0.35 to 0.42 water-to-binder ratio (W/B), 10% to 40% of pulverised fuel ash (PFA) as replacement of cement by mass, 0.02 to 0.06% of viscosity enhancer admixture (VEA), by mass of binder, and 0.3 to 1.2% of superplasticizer (SP), by mass of binder. The derived models that enable the identification of underlying primary factors and their interactions that influence the modelled responses of composite cement paste are presented. Such parameters can be useful to reduce the test protocol needed for proportioning of composite cement paste. This paper attempts also to demonstrate the usefulness of the models to better understand trade-offs between parameters and compare the responses obtained from the various test methods which are highlighted. The multi parametric optimization is used in order to establish isoresponses for a desirability function of cement composite paste. Results indicate that the replacement of cement by PFA is compromising the early compressive strength and up 26%, the desirability function decreased.

Experimental Design to Optimize High-Volume Ash Grout in the Presence of Welan Gum and Superplasticizer

Applications such as soil, rock and oil-well grouting all require enormous amounts of cement and are good examples of areas where a high volume of fly ash could partially replace cement to produce low-cost, environmentally safe and durable concrete. There is an increasing need to identify the rheological properties of cement grout using a simple test to determine the fluidity, and other properties of underwater grouts such as washout resistance and compressive strength. This paper presents statistical models developed using a fractorial design which was carried out to model the influence of key parameters on properties affecting the performance of underwater grout. Such responses of fluidity included mini-slump and flow time measured by Marsh cone, washout resistance, unit weight and compressive strength. The models are valid for mixes with 0.40 to 0.60 water-to-cementitious materials ratio, 0.02 to 0.08% of anti-washout admixture, by mass of binder, and 0.6 to 1.8% of superplasticizer, by mass of cementitious materials. The grout was made with 50% of pulverized-fuel ash replacement, by mass ofcementitious materials. Also presented are the derived models that enable the identification of underlying primary factors and their interactions that influence the modelled responses of underwater cement grout. Such parameters can be useful to reduce the test protocol needed for proportioning of underwater cement grout. This paper highlighted the influence of W/CM and dosage of antiwashout admixture and superplasticizer on fluidity, washout resistance and compressive strength and attempted also to demonstrate the usefulness of the models to improve understanding of trade-offs between parameters.

Factorial Design of Modelling Mix Proportion Parameters of Underwater Composite Cement Grouts

There is an increasing need to identify the rheological properties of cement grout using a simple test to determine the fluidity, and other properties of underwater applications such as washout resistance and compressive strength. This paper reviews statistical models developed using a factorial design that was carried out to model the influence of key parameters on properties affecting the performance of underwater cement grout. Such responses of fluidity included minislump and flow time measured by Marsh cone, washout resistance, unit weight, and compressive strength. The models are valid for mixes with 0.35–0.55 water-to-binder ratio (W/B), 0.053–0.141% of antiwashout admixture (AWA), by mass of water, and 0.4–1.8% (dry extract) of superplasticizer (SP), by mass of binder. Two types of underwater grout were tested: the first one made with cement and the second one made with 20% of pulverised fuel ash (PFA) replacement, by mass of binder. Also presented are the derived models that enable the identification of underlying primary factors and their interactions that influence the modelled responses of underwater cement grout. Such parameters can be useful to reduce the test protocol needed for proportioning of underwater cement grout. This paper attempts also to demonstrate the usefulness of the models to better understand trade-offs between parameters and compare the responses obtained from the various test methods that are highlighted.

Nonmarket Capabilities and the Prosecution of Trade Remedy Cases in the United States

The study investigates the prosecution of US trade remedy cases as examples of administrative government agency investigations and seeks to identify key capabilities for effective corporate political strategy targeting these institutions. Trade remedy cases are important policy tools, designed to protect domestic firms from ‘unfair’ import competition. The research contributes to the growing literature on corporate political activity and its links with superior outcomes in the marketplace. Three capabilities are identified: the capability to collect market/non-market intelligence, the capability to build and shape the administrative record, and the capability to align business practice with the US trade remedy institutions.

A microbial fuel cell in contaminated ground delineated by electrical self-potential and normalized induced polarization data

There is a growing interest in the use of geophysical methods to aid investigation and monitoring of complex biogeochemical environments, for example delineation of contaminants and microbial activity related to land contamination. We combined geophysical monitoring with chemical and microbiological analysis to create a conceptual biogeochemical model of processes around a contaminant plume within a manufactured gas plant site. Self-potential, induced polarization and electrical resistivity techniques were used to monitor the plume. We propose that an exceptionally strong (>800 mV peak to peak) dipolar SP anomaly represents a microbial fuel cell operating in the subsurface. The electromagnetic and electrical geophysical data delineated a shallow aerobic perched water body containing conductive gasworks waste which acts as the abiotic cathode of microbial fuel cell. This is separated from the plume below by a thin clay layer across the site. Microbiological evidence suggests that degradation of organic contaminants in the plume is dominated by the presence of ammonium and its subsequent degradation. We propose that the degradation of contaminants by microbial communities at the edge of the plume provides a source of electrons and acts as the anode of the fuel cell. We hypothesize that ions and electrons are transferred through the clay layer that was punctured during the trial pitting phase of the investigation. This is inferred to act as an electronic conductor connecting the biologically mediated anode to the abiotic cathode. Integrated electrical geophysical techniques appear well suited to act as rapid, low cost sustainable tools to monitor biodegradation.

Solving exchange rate puzzles with neither sticky prices nor trade costs

We present a simple framework in which both the exchange rate disconnect and forward bias puzzles are simultaneously resolved. The flexible-price two-country monetary model is extended to include a consumption externality with habit persistence. Habitpersistence is modeled using Campbell Cochrane preferences with ‘deep’ habits along the lines of the work of Ravn, Schmitt-Grohe and Uribe. By deep habits, we mean habits defined over goods rather than countries. The model is simulated using the artificial economy methodology. It offers a neo-classical explanation of the Meese–Rogoff puzzle and mimics the failure of fundamentals to explain nominal exchange rates in a linear setting. Finally, the model naturally generates the negative slope in the standard forward market regression.

Motivational trade-offs and potential pain experience in hermit crabs

One criterion of pain experience is that the emotional response to pain may be traded-off against other motivational requirements. This was tested in hermit crabs, housed in either preferred or unpreferred species of shells, by subjecting their abdomens to electric shocks of gradually increasing intensity. The first observable response was not affected by shell species but those in preferred shells evacuated at a higher shock level than those in poor quality shells. Thus, they seem to trade-off the requirement to retain a high quality shell with that of avoidance of the noxious stimulus. Some crabs returned to their shells and those that got back into the preferred species did so with less probing of the aperture before getting in and subsequently thrust their abdomen in and out less often in further investigation, thus confirming their shell species preference. Not all crabs returned to the vicinity of the shell and some attempted to climb the wall of the experimental chamber. Others engaged in shell rapping as if in a fight and grooming of the abdomen was noted. These findings are consistent with the idea of a pain experience rather than a nociceptive reflex. (C) 2009 Elsevier B.V. All rights reserved.