Effect of Curing Conditions on the Strength Development of Alkali-Activated Mortar

In this study, the strength development and microstructure evolution of alkali-activated fly ash (AAF), granulated blast furnace slag (AAG), and metakaolin (AAM) mortars under standard curing, steam curing, and oven curing conditions were investigated. The results show that 80 °C steam curing was more suitable for AAF mortar. Although oven curing was not as good as steam curing under the same temperature, the water evaporation increased the volume density of the N-A-S-H gel and refined the pore structure. For AAG mortar, the strength developed according to a Boltzmann function with time under steam curing conditions, which increased rapidly in the first 8 h, but grew little after about 15 h. Moreover, the strength development was severely limited by steam curing at 60 °C, and decreased under oven curing conditions due to the formation of microcracks that were induced by temperature stress and chemical shrinkage. For AAM mortar, the strength developed according to an Allometric power function with time under steam curing conditions, and the N-A-S-H gel formed in AAM had a higher polymerization degree and denser structure compared to that in AAF. The compressive strength of AAM mortar was 31.7 MPa after 80 °C steam curing for 4 h, and the standard curing time required to reach the same strength was less than 24 h, indicating that the standard curing was more suitable.

Response of Mechanical Properties of Polyvinyl Chloride Geomembrane to Ambient Temperature in Axial Tension

Aiming at the mechanical response of geomembrane (GEM) in membrane-faced rockfill dam (MFRD) to different ambient temperatures, the mechanical properties in axial tension of polyvinyl chloride (PVC) GEM were studied by experiment and theoretical analysis. First, fifteen groups of axial tensile tests for longitudinal/transverse specimens were conducted at different temperatures in the temperature environment laboratory, the stress–strain curve and Young’s modulus were obtained, and the variation of Young’s modulus with temperature was analyzed by Boltzmann function fitting. Second, the glass transition temperature of PVC GEM was obtained by differential scanning calorimetry (DSC), and the difference in mechanical properties between longitudinal and transverse specimens of PVC GEM was analyzed by thermomechanical analyzer (TMA) thermodynamic test. The results showed that the lower the temperature, the greater the Young’s modulus, and the smaller the linear interval of stress and strain, while the higher the temperature, the result is opposite. The difference in mechanical properties between the two directions is related to the ambient temperature. The orientation of polymer structure accounts for the difference in mechanical properties by theoretical analysis. The fitting results of Boltzmann function have a certain reference value for numerical simulation. In design of the membrane impervious structure in MFRD, the ambient temperature should be considered fully, and the longitudinal/transverse welding splicing should be avoided as far as possible. The current test specification should test the mechanical performance of GEM at normal operating temperature of reservoir instead of the test and quality evaluation at a single temperature. The temperature should be considered comprehensively in construction to avoid damaging the performance of impervious structure and ensure the service life.

A Validation Study on the Simultaneous Quantification of Multiple Wine Aroma Compounds with Static Headspace-Gas Chromatography-Ion Mobility Spectrometry (SHS-GC-IMS)

A new quantitative method based on static headspace−gas chromatography−ion mobility spectrometry (SHS−GC−IMS) is proposed, which enables the simultaneous quantification of multiple aroma compounds in wine. The method was first evaluated for its stability and the necessity of using internal standards as a quality control measure. The two major hurdles in applying GC-IMS in quantification studies, namely, non-linearity and multiple ion species, were also investigated using the Boltzmann function and generalized additive model (GAM) as potential solutions. Metrics characterizing the model performance, including root mean squared error, bias, limit of detection, limit of quantification, repeatability, reproducibility, and recovery were investigated. Both non-linear fitting methods, Boltzmann function and GAM, were able to return desirable analytical outcomes with an acceptable range of error. Potential pitfalls that would cause inaccurate quantification i.e., effects of ethanol content and competitive ionization, were also discussed. The performance of the SHS-GC-IMS method was subsequently compared against a currently established method, namely, GC-MS, using actual wine samples. These findings provide an initial validation of a GC-IMS-based quantification method, as well as a starting point for further enhancing the analytical scope of GC-IMS.

A Validation Study on the Simultaneous Quantification of Multiple Wine Aroma Compounds with Static Headspace-Gas Chromatography-Ion Mobility Spectrometry (SHS-GC-IMS)

<p>A new quantitative method based on static headspace−gas chromatography−ion mobility spectrometry (SHS−GC−IMS) is proposed, which enables the simultaneous quantification of multiple aroma compounds in wine. The method was first evaluated for its stability and the necessity of using internal standards as a quality control measure. The two major hurdles in applying GC-IMS in quantification studies, namely, non-linearity and multiple ion species, were also investigated using the Boltzmann function and generalized additive model (GAM) as potential solutions. Metrics characterizing the model performance, including root mean squared error, bias, limit of detection, limit of quantification, repeatability, reproducibility, and recovery were investigated. Both non-linear fitting methods, Boltzmann function and GAM, were able to return desirable analytical outcomes with an acceptable range of error. A potential pitfall that would cause inaccurate quantification <i>i.e.</i>, competitive ionization, is also discussed. These findings provide an initial validation of a GC-IMS-based quantification method, as well as a starting point for further enhancing the analytical scope of GC-IMS.</p>

A Validation Study on the Simultaneous Quantification of Multiple Wine Aroma Compounds with Static Headspace-Gas Chromatography-Ion Mobility Spectrometry (SHS-GC-IMS)

<p>A new quantitative method based on static headspace−gas chromatography−ion mobility spectrometry (SHS−GC−IMS) is proposed, which enables the simultaneous quantification of multiple aroma compounds in wine. The method was first evaluated for its stability and the necessity of using internal standards as a quality control measure. The two major hurdles in applying GC-IMS in quantification studies, namely, non-linearity and multiple ion species, were also investigated using the Boltzmann function and generalized additive model (GAM) as potential solutions. Metrics characterizing the model performance, including root mean squared error, bias, limit of detection, limit of quantification, repeatability, reproducibility, and recovery were investigated. Both non-linear fitting methods, Boltzmann function and GAM, were able to return desirable analytical outcomes with an acceptable range of error. A potential pitfall that would cause inaccurate quantification <i>i.e.</i>, competitive ionization, is also discussed. These findings provide an initial validation of a GC-IMS-based quantification method, as well as a starting point for further enhancing the analytical scope of GC-IMS.</p>

Comparative analysis of methods for studying soot sediments at fire places

Introduction. Smokes are aerosols that contain sublimating substances and condensing vapors, as well as products of chemical and photochemical reactions. In addition to solid and liquid particles, they contain gaseous products of both complete and incomplete decomposition during combustion process, as well as nitrogen and the remains of unreacted oxygen during combustion. The aerosol substance of smoke that has settled on any surface is called soot, which often acts as an object of fire-technical expertise, and the aggregate of soot particles that form zones of various configurations is called smokiness. Goals and objectives. The aim of the work is to study soot and its components for the development of a comprehensive methodology for the study of fires in determining both the focus and the cause of the fire, as well as the pathways of the spread of hazardous factors of fire at different stages of fire development. The main task of the work is to determine the dependence of the qualitative and quantitative indicators of soot and its component composition on the temperature conditions of combustion of various materials in order to establish the conditions for the course of a fire. Research methods. Field and laboratory methods for the study of soot are considered. Field methods include visual analysis of soot deposits (identifying the configuration of soot, color and intensity of the soot layer) and measuring the electrical resistance of the soot layer using a field contact probe. Laboratory methods include the method of microscopic morphological analysis, the method of thermal analysis, molecular spectroscopy and gas chromatography, which are indirect and direct methods for studying extracted organic components of soot. Results and its discussion. The modern methods of research of soot are analyzed. A scheme of laboratory methods is proposed. It allows carry out full morphological analysis, to evaluate the behavior of soot components during heating and composition of extracted components for solving the problems of studying fires. Regression dependences of the content of bituminous components on the logarithm of the electrical resistance of the soot layer were obtained, which showed that, regardless of the type of combustible material, a transition zone is observed on them, in which, with a relatively small change in electrical resistance, a significant increase in the content of bituminous components is observed. Conclusion. The paper considers an comprehensive approach to the study of extractable components of soot. The obtained dependences of the qualitative and quantitative indicators of soot and its component composition on the temperature conditions of combustion of various materials will improve the quality and level of reliability of information in the study of fires in order to determine the focus and cause of a fire, as well as the ways of spreading hazardous factors of a fire at different stages of its development. Key words: smoke, soot, extractable organic compounds, bitumen components, soot layer electrical resistance, molecular spectroscopy, Boltzmann function, fire investigation.

A modified choice function hyper-heuristic with Boltzmann function

Hyper-heuristics are a subclass of high-level research methods that function in a low-level heuristic research space. Their aim objective is to improve the level of generality for solving combinatorial optimization problems using two main components: a methodology for the heuristic selection and a move acceptance criterion, to ensure intensification and diversification [1]. Thus, rather than working directly on the problem's solutions and selecting one of them to proceed to the next step at each stage, hyper-heuristics operates on a low-level heuristic research space. The choice function is one of the hyper-heuristics that have proven their efficiency in solving combinatorial optimization problems [2–4]. At each iteration, the selection of heuristics is dependent on a score calculated by combining three different measures to guarantee both intensification and diversification for the heuristics choice process. The heuristic with the highest score is therefore chosen to be applied to the problem. Therefore, the key to the success of the choice function is to choose the correct weight parameters of its three measures. In this study, we make a state of the art in hyper-heuristic research and propose a new method that automatically controls these weight parameters based on the Boltzmann function. The results obtained from its application on five problem domains are compared with those of the standard, modified choice function proposed by Drake et al. [2,3].

Assessment of Three Mathematical Prediction Models for Forecasting the COVID-19 Outbreak in Iran and Turkey

COVID-19 pandemic has become a concern of every nation, and it is crucial to apply an estimation model with a favorably-high accuracy to provide an accurate perspective of the situation. In this study, three explicit mathematical prediction models were applied to forecast the COVID-19 outbreak in Iran and Turkey. These models include a recursive-based method, Boltzmann Function-based model and Beesham’s prediction model. These models were exploited to analyze the confirmed and death cases of the first 106 and 87 days of the COVID-19 outbreak in Iran and Turkey, respectively. This application indicates that the three models fail to predict the first 10 to 20 days of data, depending on the prediction model. On the other hand, the results obtained for the rest of the data demonstrate that the three prediction models achieve high values for the determination coefficient, whereas they yielded to different average absolute relative errors. Based on the comparison, the recursive-based model performs the best, while it estimated the COVID-19 outbreak in Iran better than that of in Turkey. Impacts of applying or relaxing control measurements like curfew in Turkey and reopening the low-risk businesses in Iran were investigated through the recursive-based model. Finally, the results demonstrate the merit of the recursive-based model in analyzing various scenarios, which may provide suitable information for health politicians and public health decision-makers.