The Influence of the Environment on the Properties of Hybrid Cement-Based Concrete with Steel and Air-Cooled Slags

This article presents the results of research that dealt with the development of non-traditional concrete using a hybrid alkali-activated cement. It is concrete based on by-products from a metallurgical plant that replaced 100% of the natural aggregates. Steel slag (CSS, fraction: 0/8 mm) was used as a filler in combination with air-cooled slag (ACBFS, fraction: 8/16 mm and 16/32 mm). Portland blended cement (CEM II/B-S 42.5N) and H-CEMENT were used as binding components in the development of the concrete mixture designs. Both of these cements were produced by Považská cementáreň, a.s., Ladce. Attention was focused on testing the physical and mechanical properties of the developed concretes in various environments. An aqueous environment was selected as the first environment for the placement of test specimens (cubes with 150 mm edges and prisms with dimensions of 100 × 100 × 400 mm3) according to the ČSN EN 206-1 standard and the outdoor environment (August to October). The determination of the cube strength was made after 7, 28, and 90 days, the determination of the flexural and compressive strength was made at the end of the prisms, and the determination of the dynamic modulus of elasticity was made after 28 days on the prisms. The test results of the test specimens, which were placed in two environments, were compared and it was found that, after 90 days, the outdoor environment caused a decrease in the concrete’s strength characteristics when using Portland blended cement (CEM II/ B-S 42.5N) of about 8%; in contrast, when using H-CEMENT, the concrete’s strength increased by about 14%. The use of H-CEMENT and the addition of PUZZOLANIT in the amount of 30% in combination with CEM II/B-S 42.5N in the amount of 70% reduced the decrease in the strength of the concrete after 90 days by about 3%. The research results confirm the suitability of using H-CEMENT and the addition of PUZZOLANIT for the production of concrete based on steel slag (CSS) and air-cooled slag (ACBFS).

Recent Applications of Mixture Designs in Beverages, Foods, and Pharmaceutical Health: A Systematic Review and Meta-Analysis

Design of Experiments (DoE) is a statistical tool used to plan and optimize experiments and is seen as a quality technology to achieve products excellence. Among the experimental designs (EDs), the mixture designs (MDs) stand out, being widely applied to improve conditions for processing, developing, or formulating novel products. This review aims to provide useful updated information on the capacity and diversity of MDs applications for the industry and scientific community in the areas of food, beverage, and pharmaceutical health. Recent works were selected following the Preferred Reporting Items for Systematic Review and Meta-Analyses statement (PRISMA) flow diagram. Data analysis was performed by self-organizing map (SOM) to check and understand which fields of application/countries/continents are using MDs. Overall, the SOM indicated that Brazil presented the largest number of works using MDs. Among the continents, America and Asia showed a predominance in applications with the same amount of work. Comparing the MDs application areas, the analysis indicated that works are prevalent in food and beverage science in the American continent, while in Asia, health science prevails. MDs were more used to develop functional/nutraceutical products and the formulation of drugs for several diseases. However, we briefly describe some promising research fields in that MDs can still be employed.

Ruggedness Evaluation and Precision Estimates for Newly Developed Test Methods for Asphalt-Treated Cold Recycled Pavements

Asphalt-treated cold recycled pavements, including cold in place recycling, full depth reclamation, and cold central plant recycling, are becoming popular rehabilitation options because they are economical, sustainable, and provide good performance. Because asphalt-treated cold recycled pavements use foamed or emulsified binder, they require a curing period post-construction before being opened to traffic or surfaced. Uniform guidelines on when an asphalt-treated cold recycled roadway can be opened to traffic or surfaced are not widely established, many are based on time or moisture content, and extreme ranges exist among agency specifications. Mixture designs also vary widely among agencies with regard to active filler use and asphalt recycling agents, further complicating the determination of necessary curing time. NCHRP Project 09-62 investigated a variety of test methods for determining when a recycled roadway could be opened to traffic or surfaced. This included extensive laboratory and field evaluations. New shear strength and raveling test methods were developed. For each test method a ruggedness study and inter-laboratory study were performed. The ruggedness study revealed critical test fixture and operation parameters. Six asphalt-treated cold recycled pavement process/material combinations were tested by three entities to develop precision estimates and statements (i.e., repeatability and reproducibility) for the new test methods. Tools and information from this study provide a rational basis for establishing specifications, which will help reduce pavement damage from early traffic and minimize roadway closures and delays.

Experimental and Informational Modeling Study on Flexural Strength of Eco-Friendly Concrete Incorporating Coal Waste

Construction activities have been a primary cause for depleting natural resources and are associated with stern environmental impact. Developing concrete mixture designs that meet project specifications is time-consuming, costly, and requires many trial batches and destructive tests that lead to material wastage. Computational intelligence can offer an eco-friendly alternative with superior accuracy and performance. In this study, coal waste was used as a recycled additive in concrete. The flexural strength of a large number of mixture designs was evaluated to create an experimental database. A hybrid artificial neural network (ANN) coupled with response surface methodology (RSM) was trained and employed to predict the flexural strength of coal waste-treated concrete. In this process, four influential parameters including the cement content, water-to-cement ratio, volume of gravel, and coal waste replacement level were specified as independent input variables. The results show that concrete incorporating 3% recycled coal waste could be a competitive and eco-efficient alternative in construction activities while attaining a superior flexural strength of 6.7 MPa. The RSM-modified ANN achieved superior predictive accuracy with an RMSE of 0.875. Based on the experimental results and model predictions, estimating the flexural strength of concrete incorporating waste coal using the RSM-modified ANN model yielded superior accuracy and can be used in engineering practice to save the effort, cost, and material wastage associated with trial batches and destructive laboratory testing while producing mixtures with enhanced flexural strength.

Background, Applications and Issues of the Experimental Designs for Mixture in the Food Sector

Background: Mixtures play a key role in Food Science and Technology. For studying them, rational approaches should be used. In detail, the experimental designs for mixtures are useful tools for studying the effects of ingredients/components in formulations. Results: Food Science and Technology is the fourth category among the total records considered in this review. The applications span from food formulation to the composition of modified atmosphere, shelf-life improvement and bioactives extraction. However, the majority of the studies regards few products and ingredients. Simplex-lattice and simplex-centroid designs are the most common used, although some optimal designs, such as the D-optimal, have also interesting applications. Finally, some issues are highlighted, which basically regard the interpretation of the models coefficients and the lack of model validation. Conclusion: In the last decade, mixture designs have been fairly used in the field of Food Science and Technology. Modeling the response(s) allows researchers to achieve a global knowledge of the system under study within the defined experimental domain. However, the majority of application has regarded limited classes of products, and thus an increase in the spectrum of applications is desired.

D-OPTIMAL RESPONSE MIXTURE DESIGN MODELING OF POLYSTYRENE WASTE ADHESIVE FORMULATIONS

The importance of polystyrene in handling and transportation of fragile equipment for safe delivery cannot be under stated. However; the post-usage has raised serious concern due to adverse effects caused by the litters on environment in blocking water-ways due to its weightlessness, release of oxides of carbon and resisting decomposition among others. This work was intended to model produced adhesive from polystyrene waste using Design Expert version 6.0.8 software and D-optimal mixture design for the responses analyses to obtain the best adhesive. Eight (8) experimental runs were generated for resin formulations with only 3 feasible, coded: R1, R4 and R7, based on 2 factorial design of experiment for resin formulations. Furthermore, 14 adhesive formulations were generated for each resin, coded: R1AD, R4AD and R7AD, that is, the formulated resin was combined with additives to produce adhesive using 3 factorial mixture designs and 4 responses, namely: viscosity, pH, percentage moisture content and percentage solid content. The responses were modeled using D-optimal mixture design: the viscosity response modeling was best fitted with quadratic model for R1AD produced adhesives, while R4AD and R7AD produced adhesives were fitted with Cubic model. The pH, percentage moisture content and percentage solid content responses were all fitted with cubic model based on the statistical and modeled data. The modeling solution was further optimized and validated for the three adhesive productions, the general selection of produced adhesive based on desirability factor and line with experimental analyses from the responses shows: R7AD2>R4AD1>R1AD1 produced adhesives in the order of fitness.