The present work focuses on the modeling and analysis of mechanical properties of structural steel. The effect of major alloying elements

namely carbon, manganese and silicon has been investigated on mechanical properties of structural steel. Design of experiments is used to

develop linear models for the responses namely Yield strength, Ultimate tensile strength and Elongation. The experiments have been

conducted as per the full factorial design where all process variables are set at two levels. The main effect plots showed that the alloying

elements Manganese and Silicon have positive contribution on Ultimate tensile strength and Yield strength. However, Carbon and

Manganese showed more contribution as compared to Silicon. All three alloying elements are found to have negative contribution

towards the response- Elongation. The present work is found to be useful to control the mechanical properties of structural steel by varying

the major alloying elements. Minitab software has been used for statistical analysis. The linear regression models have been tested for the

statistical adequacy by utilizing ANOVA and statistical significance test. Further, the prediction capability of the developed models is

tested with the help of test cases. It is found that all linear regression models are found to be statistically adequate with good prediction

capability. The work is useful to foundrymen to choose alloying elements composition to get desirable mechanical properties.

Catalytic reforming is an important intermediate in the processing of crude (naphtha in particular) to obtain gasoline. The catalyst used in the process (platinum) is quite expensive and may negatively impact the business if not used judiciously. The aforesaid not only refers to the reduction in loss of the catalyst per unit of gasoline produced but also to the manufacturing of an environmentally friendlier product alongside which is the need of the planet and also a necessity to meet the increasingly strict government norms. In order to meet the above requirements, various refineries around the world use various well-known conventional methods which depend on the quality and quantity of crude manufactured by them.
This paper focuses on highlighting recent advancements in methods of catalytic regeneration (CR) in the reforming unit of petroleum industries to produce high octane gasoline, without any major replacements in their existing setup. Research papers formulated by the application of methodologies involving non-linear models and real-time refinery data have only been considered to avoid any deviations/errors in practical applications. In-depth analysis of these papers has led to the origin of some ideas which have been included as suggestions and can be considered as subjects of further research. In all, the objective of the paper is to serve as a reference for researchers and engineers working on devising optimum methods to improve the regeneration of reforming catalysts.

Despite many years of development in the field of rotor dynamics, many issues still need to be resolved. This is due to the fact that turbomachines, even those with low output power, have a very complex design. The author of this article would like to signal these issues in the form of several questions, to which there are no precise answers. The questions are as follows: How can we build a coherent dynamic model of a turbomachine whose some subsystems have non-linear characteristics? How can we consider the so-called prehistory in our analysis, namely, the relation between future dynamic states and previous ones? Is heuristic modelling the future of rotor dynamics? What phenomena may occur when the stability limit of the system is exceeded? The attempt to find answers to these questions constitutes the subject of this article. There are obviously more similar questions, which encourage researchers from all over the world to further their research.

Estymacja metodą najmniejszych kwadratów (LS) jest Jednym z najważniejszych narzędzi w analizowaniu danych geodezyjnych. Jednakże powszechne korzystanie z rej metody nie zawsze idzie w parze z pełnym uświadomieniem sobie jej podstaw. W standardowym formalizmie teorii estymacji LS w rzeczywistości istnieje kilka paradoksalnych i osobliwych zagadnień rzadko formułowanych wprost. Celem niniejszej pracy jest przedstawienie niektórych z tych zugadnień i przedyskutowanie ich konsekwencji w analizie danych gcodezyjnvch oraz problematyce estymacji parametrów. W pierwszej części pracy przedstawiony Jest alternatywny pogląd na podstawy statystyczne, które są tradycyjnie łączone z estymacją LS. W SZC7.ególności pokazano. że właściwość nieobciąźoności dla zwykłych estymatorów LS może być zastąpiona przez inne. równowazne JeJ uwarunkowanie, które powoduje, że zakres numeryczny nieznanych parametrów jest nieograniczonv. \V drugiej części pracy przedstawiono wady meiodv LS 7. czysto algebraicznego punktu widzenia. bez uwzględnienia pojęć z zakresu prot abilisryczncgo/sratysrycznego teorii estymacji. W szczególności ,, yjaśnione zostało. cło czego odnosi się 'najmnicjsz, · (least) w metodzie najmniejszych kwadratów. Z pewnością nie odnosi się cło błędów· wyznaczanych parametrów modelu. Ponadto stwierdzono, że w bielej inwersji modelu liniowego opartej na metodzie LS istnieje krytyczna zamiana pomiędzy normami euklidesowymi błędów wyznaczanych parametrów i wyrównanych residuów.

We studied the thermophilous grass Bromus erectus in Central Europe to determine its pattern of population genetic structure and genetic diversity, using ISSR-PCR fingerprinting to analyze 200 individuals from 37 populations. We found three genetic groups with a clear geographic structure, based on a Bayesian approach. The first group occurred west and south of the Alps, the second east and north of the Alps, and the third was formed by four genetically depauperated populations in Germany. The populations from Germany formed a subset of the Bohemian-Moravian populations, with one private allele. Two differentiation centers, one in the Atlantic- Mediterranean and the second in the Pannonian-Balkan area, were recognized by species distribution modeling. The geographic distribution of the genetic groups coincides with the syntaxonomic split of the Festuco-Brometea class into the Festucetalia valesiaceae and Brometalia erecti orders. We found a statistically significant decrease in mean ISSR bands per individual from south to north, and to a lesser extent from the east to west. The former was explained by Holocene long-distance migrations from southern refugia, the latter by the difference in the gradient of anthropopression. We hypothesize a cryptic northern shelter of the species in Central Europe in the putative Moravian-Bohemian refugium.

The study makes an attempt to model a complete vibrating guitar including its non-linear features, specifically the tension-compression of truss rod and tension of strings. The purpose of such a model is to examine the influence of design parameters on tone. Most experimental studies are flawed by uncertainties introduced by materials and assembly of an instrument. Since numerical modelling of instruments allows for deterministic control over design parameters, a detailed numerical model of folk guitar was analysed and an experimental study was performed in order to simulate the excitation and measurement of guitar vibration. The virtual guitar was set up like a real guitar in a series of geometrically non-linear analyses. Balancing of strings and truss rod tension resulted in a realistic initial state of deformation, which affected the subsequent spectral analyses carried out after dynamic simulations. Design parameters of the guitar were freely manipulated without introducing unwanted uncertainties typical for experimental studies. The study highlights the importance of acoustic medium in numerical models.

Statistical analysis is helpful for better understanding of the processes which take place in agricultural ecosystems. Particular attention should be paid to the processes of crops’ productivity formation under the influence of natural and anthropogenic factors. The goal of our study was to provide new theoretical knowledge about the dependence of vegetable crops’ productivity on water supply and heat income. The study was conducted in the irrigated conditions of the semi-arid cold Steppe zone on the fields of the Institute of Irrigated Agriculture of NAAS, Kherson, Ukraine. We studied the historical data of productivity of three most common in the region vegetable crops: potato, tomato, onion. The crops were cultivated by using the generally accepted in the region agrotechnology. Historical yielding and meteorological data of the period 1990–2016 were used to develop the models of the vegetable crops’ productivity. We used two approaches: development of pair linear models in three categories (“yield – water use”, “yield – sum of the effective air temperatures above 10°C”); development of complex linear regression models taking into account such factors as total water use, and temperature regime during the crops’ vegetation. Pair linear models of the crops’ productivity showed that the highest effect on the yields of potato and onion has the water use index (R2 of 0.9350 and 0.9689, respectively), and on the yield of tomato – temperature regime (R2 of 0.9573). The results of pair analysis were proved by the multiple regression analysis that revealed the same tendencies in the crop yield formation depending on the studied factors.

Today’s electricity management mainly focuses on smart grid implementation for better power utilization. Supply-demand balancing, and high operating costs are still considered the most challenging factors in the smart grid. To overcome this drawback, a Markov fuzzy real-time demand-side manager (MARKOV FRDSM) is proposed to reduce the operating cost of the smart grid system and maintain a supply-demand balance in an uncertain environment. In addition, a non-linear model predictive controller (NMPC) is designed to give a global solution to the non-linear optimization problem with real-time requirements based on the uncertainties over the forecasted load demands and current load status. The proposed MARKOV FRDSM provides a faster scale power allocation concerning fuzzy optimization and deals with uncertainties and imprecision. The implemented results show the proposed MARKOV FRDSM model reduces the cost of operation of the microgrid by 1.95%, 1.16%, and 1.09% than the existing method such as differential evolution and real coded genetic algorithm and maintains the supply-demand balance in the microgrid.