bluuebunny/crossref_metadata_2025_split huggingface dataset:
Method for selecting geothermal energy extraction technologies using nomograms
Authors: Gabdrakhmanova K F , Izmaylova G R , Larin P A , Kuleshova L S 
Published: November 2019

Abstract
The article analyzes the efficiency of geothermal energy extraction method. Different regions of the Russian Federation were analyzed. Available geothermal energy extraction technologies using nomograms were analyzed. The nomograms describe the dynamics of outlet changes in temperatures and the amount of energy produced at various coefficients of thermal conductivity and heat capacity of rocks. The nomograms used for selection of suitable geothermal energy production technologies depending on geological and physical conditions were developed. Based on geological and physical characteristics of the bottomhole formation zone, such well parameters as the radii of the casing and the tubing and coolant velocity, outlet temperatures and thermal capacity of the well were calculated. The more efficient technology was selected.
Use of information technologies of management in public authorities activities
Authors: Kokhanovskaya I.I. , Fatykhova A.L. , Suleimanova F.M. , Golovneva E.V. 
Published: November 2019

Abstract
At present, the state is striving to introduce modern information technologies into the sphere of interaction between the government and society, since this allows for more dynamic interaction between the state, municipalities, citizens and organizations and encourages the increase in the stability and sustainability of power relations in society. While developing the state apparatus, the role of information technologies has taken on increased significance as one of the tools to promote management decisions aimed at ensuring the greater efficiency of the state.
An integrated model as a tool for implementing an enterprise management method
Authors: Lipatova S V , Yardaeva M N , Lutoshkin I V , Polyanskov Yu V 
Published: November 2019

Abstract
An integrated enterprise management model based on information about enterprise activities was developed. The integrated model formalizes enterprise management methods, including information systems caused by digitization of production and the economy as a whole and involves implementation and consolidation of effective management methods which can be adapted to changing conditions at the information systems level. The problem of labor-intensive implementation and development of information systems which requires phase implementation (phasing involves decomposition) is solved by constructing a model structure divided into levels and sub-models. This approach to the model structure can be used for phased implementation based on the analysis of the KPI system, business processes and the organizational structure of the enterprise. The complex model is a tool for implementing the management method and analysis of structural functional description of enterprise’s activities. The analysis results indicate the need for reorganization, changes in business processes or modification of key indicators.
Economic efficiency of management automation in educational organizations
Authors: Alenicheva T S , Mamaeva N A , Patlasov O Yu 
Published: November 2019

Abstract
The problem of using management automation in digital educational organization environment is considered in the article. The purpose of research is calculation of management automation performance indicators and rationale of using them. The empirical method of comparison, theoretical methods for forming a structure, making a conclusion about the composition, such as study, synthesis, analysis, are used in the article. The article is based on domestic and foreign research about information technologies in educational service management problems. The results consist in calculation of management automation performance indicators and allow justifying the position about using management automation in an educational organization based on Omsk State Railway University. The authors believe that the result of the research can be used in science and pedagogical activity concerning informational systems in the educational process and management automation in educational organization problems and digital educational environment development.
Methodology of probabilistic modelling of the current activity of industrial enterprises
Authors: Drapalyuk M V , Bezrukova T L , Shanin I I , Bezrukov B A 
Published: November 2019

Abstract
The article discusses the approach to the methodology of modeling and forecasting the production activities of industrial enterprises. It uses mathematical probability theory. All the studies are made by the example of the furniture industry enterprises. This approach enables to carry out effective planning of production and commercial activities. It also contributes to an increase in the effectiveness of marketing activities and decision making. The presented results have been achieved through the use of mathematical models and tools based on the application of the approach to defining the probability of non-zero demand for the goods. The developed mathematical models make it possible to prepare the initial data and make effective management decisions based on them in the form of plans and programs of industrial activities in a quick manner. The enterprises producing goods or providing services in a large assortment are forced to conduct a comparative mathematical analysis of the business units of the industrial enterprise in order to make a decision on the distribution of investment resources. The priority field of enterprise activity (which brings the maximum profit) receives the maximum financial investments.
Identifying duplicated ads on property selling and renting websites
Authors: Tynchenko V S , Kukartsev V V , Tynchenko V V , Bukhtoyarov V V , Chzhan E A , Kukartsev V A , Boyko A A 
Published: November 2019

Abstract
The article presents a solution for the problem of identifying duplicated ads on property selling websites. This task is formulated in the form of a classification problem: the input parameters are identified then divided into basic and non-basic, as well as a class-forming feature. It is also necessary to consider the preliminary data of processed property objects, which is necessary for proper application of the classification methods. The following is a brief review of chosen modern algorithms for solving classification problems, namely: decision trees, artificial neural networks, logistic regression. As a result of experiments, it was revealed that Artificial neural network gives the most accurate result therefore, this algorithm is suitable for the solution of the stated problem.
Mathematical competence development of bachelor of engineering
Authors: Vinogradova M , Malchukova N , Dorofeev S 
Published: November 2019

Abstract
The authors of this article draw attention to the fact that engineering education requires deep knowledge in mathematics and its methods that are fundamental for many disciplines and contribute to the development of a fundamental system of training students during their university study. Attention is focused on the need to introduce heuristic professional tasks into the studying process that develop mathematical competence among students, which includes motivational, value-based, cognitive, activity-based, reflexive and evaluative aspects. The need for the development of mathematical competence that increases intellectual base of a competitive specialist in modern society is determined in the article.
Infrastructure as a service for a digital factory, smart factory and virtual factory of the Industry 4.0
Authors: Zakoldaev D A , Korobeynikov A G , Shukalov A V , Zharinov I O 
Published: November 2019

Abstract
The task is to create an infrastructure cloud service to support informatively the completion of project and production tasks in the Industry 4.0 companies. Infrastructure digital factory service has some program components which are necessary to create digital twins of items and cyber and physical systems. Infrastructure smart factory service has some components which are necessary for completion manufacturing of technological operations of the item in automatic mode with cyber and physical equipment. Infrastructure virtual factory service has some components which are necessary to control the item during its remote exploitation by personnel. There is a scheme how to organize cloud infrastructure which is the same for smart and digital factories which are the parts of the Industry 4.0 virtual factory.
Robotic system development using CAD/CAM/CAE of NX
Authors: Anciferov S I , Gaponenko E V , Kuzmina V S 
Published: November 2019

Abstract
The article proposes a design technique of a 6DoF robotic system for processing complex-shaped parts containing a base and a module for installing a tool and a module for processing parts made in the form of parallel structure mechanisms using the CAD / CAM / CAE of NX system controlled by PLM management of Teamcenter system. In order to create a digital model of the system, a control structure was developed, which allowed creating the design using the “Bottom-Up” method in the course of the assembly. The control structure reduces the time of the creation of a model. The constructed model of the system will be used in the future for engineering calculations and mathematical analysis, as well as for obtaining all the necessary design documentation.
A realization of the turbulent vortex dynamo in the atmosphere: based on the 21st century knowledge
Authors: Levina G V 
Published: November 2019

Abstract
A brief summary of the results of numerical modeling undertaken to substantiate the action of the turbulent vortex dynamo (TVD) in the atmosphere is presented. Two series of numerical experiments are discussed. The first of them was aimed at examining a mathematical model of TVD formulated as the mean-field equations, which describe the dynamo-effect in a non-uniformly heated medium. To simulate and demonstrate the main peculiarities of the new large-scale instability in turbulence, an ingenious statement of the problem for numerical analysis was produced, namely, within a simpler framework – the Rayleigh-Bénard problem on laminar thermal convection in an extended horizontal layer. Within the second series, our developed numerical approach, used and tested in the initial series as well as obtained results therein allowed applying the TVD theory to diagnosis of tropical cyclogenesis. To this purpose, the Russian-American collaboration was initiated and the most advanced to that date tools of atmospheric analysis were utilized. Tropical cyclone formation was examined through the analysis of the American data of near-cloud-resolving (2-3 km horizontal grid spacing) atmospheric numerical simulation.
Formation of filaments and dense cores during molecular clouds collision
Authors: Rybakin B P , Moiseenko S G 
Published: November 2019

AbstractThe paper presents the results of mathematical modeling of the collision process of two molecular clouds(MC). The density distribution over the radius of the MC is modeled by various laws, the density in the center varies. The forces of gravity, thermal conductivity and radiative losses are not taken into account. The processes of deformation, fragmentation and the formation of superdense regions that occurs during the collision of molecular clouds are analyzed. Visualization of the calculation results made it possible to find the features of the emerging flow the formation of vortices, filaments, and superdense nuclei in molecular clouds.
Two-temperature advective transonic accretion flows around black holes
Authors: Sarkar Shilpa , Chattopadhyay Indranil 
Published: November 2019

Abstract
We present here unique transonic two-temperature accretion solutions in presence of radiation processes. Unlike one-temperature flow, the set of equations governing two-temperature flow is not complete, since for the latter, the number of equations is less than the number of flow variables. Consequently, a large number of transonic solutions of the equations of motion exist, for a given set of constants of motion. We invoke the second law of thermodynamics and identified the solution with the maximum entropy as the physically possible solution. In this paper, we compare spherical and rotating accretion two-temperature flows. We also show that the luminosity, as well as radiative efficiency of rotating flows, is higher by an order of magnitude, as compared to spherical flows.
Comparative analysis of prediction algorithms for building energy usage prediction at an urban scale
Authors: Ali Usman , Shamsi Mohammad Haris , Nabeel Muhammad , Hoare Cathal , Alshehri Fawaz , Mangina Eleni , Odonnell James 
Published: November 2019

AbstractStrategic planning for efficient and sustainable urban environments necessitates identification of scalable energy saving opportunities for the buildings sector. A possible resolution is the analysis of building energy use data at urban scale, although the available data is often sparse, inconsistent, diverse and heterogeneous in nature. Over the past decades, predictive modeling using sparse data has aided with the forecasting of building energy use. However, most studies of energy use prediction focus on individual buildings. This paper proposes the integration of building archetypes simulation, parametric analysis, and machine learning techniques as a solution to accurately predict individual building energy use at an urban level. The aim of the research described in this paper is to achieve accurate prediction of building energy performance, which will allow stakeholders, such as energy policymakers and urban planners, to make informed decisions when planning retrofit measures at large scale. The methodology generates synthetic building data for training the predictive model and predicts building energy use at urban scale with limited resources. The experimentation focuses on Dublin city through the development of synthetic building dataset using parametric analysis on previously identified key variables of two distinct building archetypes. Having compared different prediction algorithms, we show that the Gradient Boosted Trees algorithm gives a better prediction when compared to other algorithms.
Impact of CH2018 Climate Change Scenarios for Switzerland on today’s Swiss building stock
Authors: Buffat René , Heeren Niko , Froemelt Andreas , Raubal Martin 
Published: November 2019

Abstract
The energy demand of buildings heavily depends on outdoor temperature. Current climate change projections suggest an increase in annual mean temperatures of up to 5.4°C for Switzerland until the end of the century. In this study, an existing bottom-up building stock model is coupled with the latest spatio-temporal climate change projections. This allows for simulating the heat demand for each Swiss building for three different climate change scenarios and three periods. It is found that while space heat demand can decrease up to 33% by the end of the century, the need for air conditioning can arise. Furthermore, the impact of climate change differs between regions in Switzerland.
A Review on interdisciplinary methods for the characterization of thermal perception in public spaces
Authors: Requena-Ruiz Ignacio , Drozd Céline , Leduc Thomas , Rodler Auline , Servières Myriam , Siret Daniel 
Published: November 2019

Abstract
The contemporary design of public spaces integrates frequently urban cooling installations for thermal comfort in summertime. However, the details of the thermal experience that they provide is yet partially unknown. This paper studies how methods and techniques arising from microclimatology, urban studies and sensory studies can interact for characterizing thermal comfort outdoors. We have reviewed thirteen papers using meteorological measuring instruments and assessed them according to the requirements of methods originating from social sciences and sensory studies for the public space. As a result, we discuss the potentialities and limitations of such techniques to interact through an interdisciplinary methodological design.
Modelling the impact of green solutions upon the urban heat island phenomenon by means of satellite data
Authors: Colaninno Nicola , Morello Eugenio 
Published: November 2019

Abstract
Climate change causes a critical increase of temperature and frequency of heat waves, whose impact is particularly sensitive within the urban environment. Here, the loss of natural areas, beside morphological and thermal properties, makes urban temperature to be significantly higher compared to peri-urban and rural areas. This phenomenon is commonly known as urban heat island (UHI). Because green infrastructure provides an effective strategy for reducing the UHI effect, we explore the feasibility of remotely sensed data and statistical modelling for assessing the effectiveness of green measures. We simulated how implementing green roofs over the city of Milan could affect temperature. Geographically weighted regression has been used to model the correlation among satellite-derived vegetation map and near-surface air temperature.
Local climate impact on the energy demand: an analysis at the European scale
Authors: Krafess Ismael , Houmani Cynthia , Mauree Dasaraden , Coccolo Silvia , Perera A. T. Dasun , Scartezzini Jean-Louis 
Published: November 2019

Abstract
A reduction by 80% of the greenhouse gas emissions as well as a similar decrease for the final energy consumption is needed to respect the energy strategies and climate objectives at the European scale. To address this issue, we analysed the energy demand of 17 European cities using the coupled CIM-CitySim model. Simulations taking into account the urban microclimate were performed for one typical year to obtain the cooling and the heating demand. When comparing the results with and without the urban microclimate, although on a yearly basis there does not seem to be much difference on the overall energy demand (<15%), when looking at the seasonal dynamics, it can be noted that there are significant deviations, in particular for the cooling demand (>60%). In the future, strategies to design more sustainable urban areas at the European scale will be evaluated. The objective is to be able to define mitigation strategies that will decrease the footprint of urban areas while at the same time increasing its liveability.
The effect of Sustainable Urban Drainage Systems on outdoor comfort and runoff
Authors: Rosso Federica , Mannucci Simona , Morganti Michele , Mariani Silvia , Cecere Carlo , Ferrero Marco 
Published: November 2019

Abstract
Cities are facing numerous challenges such as Urban Heat Island Effect (UHIE) and more frequent flooding events, due to the increasing soil sealing. Greenery and water implemented in urban outdoor spaces have been promoted as effective strategies to counteract UHIE while Sustainable Urban Drainage Systems (SUDS) have been identified as convenient solutions to increase resilience to flooding. However, since many SUDS are green-based, they also benefit urban microclimate and outdoor thermal comfort. In this work, the effectiveness of SUDS as passive strategies to simultaneously improve outdoor thermal comfort and reduce stormwater runoff is assessed. The analysis is carried out on a neighbourhood in Ostia (Rome), selected as representative of Mediterranean climate. The case study area is modelled on ENVI-met in three different scenarios: the current condition is compared with two future developments in which green and water-based mitigation strategies are implemented or in which soil sealing continues based on current trend. Moreover, for each scenario, stormwater runoff has been determined using the Soil Conservation Service curve number method. Results show that the implemented mitigation strategies allow achieving improved thermal comfort conditions and at the same time they can reduce runoff.
Retrofitting a building stock: modeling and optimization for decision aiding at territory scale
Authors: Rogeau A. , Girard R. , Abdelouadoud Y. , Kariniotakis G. 
Published: November 2019

Abstract
Reduction of the energy consumption is a key lever to tackle climate change, but identification of the retrofit actions to undertake within a building stock remains a challenging scientific problem. This paper presents a complete methodology able to design action plans at a territory level with a building resolution. The economic and energetic modeling of the retrofit context is detailed before introducing a linear 0-1 optimization formulation which is used to arbitrate between both building envelope insulation and heating system replacement measures. A 500 buildings territory study case is then presented to illustrate the potential of the developed tool.
SCAFE: Automated simultaneous clustering and non-linear feature extraction of building energy profiles
Authors: Ulyanin Stepan , Vazquez-Canteli Jose , Park June Young , Nagy Zoltan 
Published: November 2019

Abstract
Increasing amounts of energy consumption data available to researchers in recent years make it easier to analyze the global energy demands. The analysis is important because buildings consume roughly 40% of global energy. One of the applications of data-driven analysis is identifying buildings that follow similar energy consumption patterns. Despite the number of available unsupervised machine learning algorithms, the user is still required to choose features, typically resorting to hourly data. In this paper, we propose we present SCAFE, an end-to-end architecture for Simultaneous Clustering And non-linear Feature Extraction. The method consists of first transforming the raw energy profiles that are represented as time-series into three channel images, using Gramian Summation, Gramian Difference and Markov Transition Fields. Then, we map the images to the latent space with the use of an autoencoder. Finally, we perform clustering in the latent space, simultaneously obtaining clusters and features of the dataset. We demonstrate SCAFE on the UTexas dataset, showing similar performance to standard k-means clustering while in addition also extracting natural features of the data in the latent space.
Takeshi: Application of unsupervised machine learning techniques for topology detection in building energy systems
Authors: Stinner Florian , Raßpe-Lange Lukas , Baranski Marc , Müller Dirk 
Published: November 2019

Abstract
Buildings rarely achieve their energy targets defined in the planning phase. Due to a lack of time and money, operators frequently fail to identify and implement energy efficiency measures in control. Knowledge about the topology of the building energy system (BES) is important for the automatic identification of energy efficiency measures, but usually does not exist in a machine-readable form. In this paper, we present an approach to detect the topology of a BES using an unsupervised learning algorithm, called Takeshi. We apply the algorithm to real and simulated time series data of a multifunctional building. This algorithm relies on a data mining approach, in which four steps are conducted, preprocessing, partitioning, sequencing and rule detection. The results obtained using the real-life data were only partly satisfactory. The best F1 score was 43,3 %, whereby the used seasons of the year had a high influence. In order to demonstrate a broader range of applications, we applied the algorithm to the simulation data. In that case, the algorithm shows significantly better results and the F1 score reached 79,6 %. We evaluate reasons for the poor performance in the case of the real BACS data set and derive possible improvements to the methodology.