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Natural ventilation is an energy efficient alternative for reducing the energy use in buildings, achieving thermal comfort and maintaining a healthy indoor environment. Differences in wind pressure along the façade and differences between indoor and outdoor temperatures create a natural air exchange between indoor and outdoor air. These physical processes are complex, and predicting ventilation rates is difficult. This paper presents a method for determining natural ventilation air flow in single-façade thermo-air system by simulating the room using the program TRNSYS 16. Theoretical checking of the airflow obtained by simulation was performed by comparing the thermal response in the room following the simulation, with interior temperatures measured during the experiment.

This paper proposes a solution for the most easily detectable type of cancer, skin cancer. Due to the ozone layer thinning, it was observed an increase in the number of skin lesion anomalies. Those anomalies are produced by the increasing UV radiation intensity. Good protection against sun is not always facile, mainly in the exposed regions of the skin like the face and the lower regions of the arms. Most types of cancers can be easily extracted via surgery if they are detected in one of the incipient development stages. Using a high resolution image, a classification algorithm can detect certain patterns in the nevi color, shape, veins or irregularities inside. Analyzing those aspects, a person can track their nevi development easily and intervene if it necessary. The originality of this paper consist in designing several convolutional neural networks, using the Python programming language, the Keras API and the Tensorflow framework alongside with proper dataset selection. The convolutional neural networks were trained using an open source dataset, with the purpose of formulating a diagnosis for new patients. The convolutional neural networks are provided with 7 classes of images, representing 7 types of skin lesions as input, and will output a diagnosis. The result of the research was a classifier with a convenient classification accuracy based on the dataset, and a medium accuracy based on new data.

In this paper, we address the position accuracy required in the User Segment. The goal is to find the required minimum distance from the provider receiver to the correction receiver. Several correction receivers, located at different distances, have been used to investigate the accuracy improvements provided to a chosen receiver, which played the role of the user. The applied method reveals valuable findings about the importance of the distance between a reference station and the user. The obtained results can be used to determine the necessary accuracy requirements for different GNSS applications.

This paper proposes a random number generator based on the quantum tunnel effect that takes place in transistors. The main system is divided into two basic components: the entropy source and the postprocessing block. The quantum tunnel effect is subjected to a random character, which means that electrons have a probability to pass through the potential barrier of the transistor. Theoretically, the measurable output current of the transistor should have a random variance in a predetermined interval, that results into a random sequence. Afterwards, the postprocessing block extracts the bias from the generated array. It is implemented through a hash function which employs the Toeplitz matrix, resulting into a true random sequence. This paper accounts the preliminary stages of development of an original random number generator. The focus was the physical phenomena, the tunnel effect in transistors, and the study of its probability with respect to the device parameters. In terms of postprocessing the main regard was choosing the adequate extraction method for the quantum entropy source. The novelty of the paper is represented by using the tunnel FET as an entropy source and finding a suitable postprocessing model for a higher generation rate.

This study deals with computational analysis of vibration isolators' behavior, using the fractional-order differential equations (FDE). Numerical investigations regarding the influences of &alpha, fractional derivatives have been mainly focused on the dissipative component within the differential constitutive equation of rheological model. Two classical models were considered, Voigt-Kelvin and Van der Pol, in order to develop analyses both on linear and nonlinear formulations. The aim of this research is to evaluate the operational capability, provided by the &alpha, fractional derivatives within the viscous component of certain rheological model, to enable an accurate response regarding the realistic behavior of elastomeric-based vibration isolators. The hysteretic response followed, which has to be able to assure the symmetry of dynamic evolution under external loads, and at the same time, properly providing dissipative and conservative characteristics in respect of the results of experimental investigations. Computational analysis was performed for different values of &alpha, fractional order, also taking into account the integer value, in order to facilitate the comparison between the responses. The results have shown the serviceable capability of the &alpha, fractional damping component to emulate, both a real dissipative behavior, and a virtual conservative characteristic, into a unitary way, only by tuning the &alpha, order. At the same time, the fractional derivative models are able to preserve the symmetry of hysteretic behavior, comparatively, e.g., with rational-power nonlinear models. Thereby, the proposed models are accurately able to simulate specific behavioral aspects of rubber-like elastomers-based vibration isolators, to the experiments.

A full-scale, three-dimensional, transient CFD modelling approach capable of predicting the three-phase fluid-flow characteristics and desulphurisation behaviour in an argon-stirred ladle was developed. The model can accurately predict the molten steel flow and slag eye behaviour. The predicted sulphur content in ladle as a function of time agrees well with the experimental data. The effects of the initial sulphur content, the gas flow rate and the slag layer thickness on the desulphurisation efficiency were also investigated. The predicted results show that the desulphurisation efficiency improves with the increase of the initial sulphur content, the gas flow rate and the slag layer thickness. Higher gas flow rate can improve the slag–steel interaction, which, in turn, helps improving the desulphurisation rate. The thinner the slag layer, the larger the slag eyes and the smaller the interfacial area between the slag and steel phases. The consequence is the decrease in the desulphurisation rate.

It has been revealed that microstructure and mechanical properties of aluminium castings can be significantly improved by adding nanoparticles as reinforcement to fabricate aluminium-based metal matrix nanocomposites (MMNCs). One of the common problems in fabricating MMNCs is the agglomeration of reinforcement nanoparticles. In the present study, ultrasonic stirring technology (UST) is deployed to assist 6061 nanocomposite casting process by promoting the dispersion and deagglomeration. Al2O3/SiC nanoparticles are used as reinforcement materials. Nanoparticles are added into the molten alloy and dispersed by ultrasonic cavitation and acoustic streaming caused by UST. The microstructure, fracture behaviour and mechanical properties of 6061-based MMNC samples have been investigated. Tensile strength and yield strength of MMNC samples remain at the same level while the elongation increases significantly compared to reference samples.

Climate change creates new challenges for preventing and protecting human health against different diseases that could appear and propagate. The Aedes albopictus mosquito species is an important vector for different diseases like dengue fever or zika. Although this species is not “indigenous” in Europe, its presence is noticed in many countries on the continent. The Ae. albopictus establishment is conditioned by the species’ characteristics and environmental factors. To assess the possible spread of Ae. albopictus in the Dobrogea region (situated in the Southeast of Romania), we conducted the following analysis: (1) Investigation of the current distribution and climatic factors favoring Ae. albopictus’ establishment in Europe, (2) Analysis of climate dynamics in Dobrogea in terms of the parameters identified at stage (1), (3) Testing the hypothesis that the climate from Dobrogea favors Ae. albopictus’ establishment in the region, (4) Building a Geographic Information System (GIS)-based model of the potential geographic distribution of Ae. albopictus in Dobrogea. Results show that the climate of Dobrogea favors the apparition of the investigated species and its proliferation.

The most common causes of accidents involving trailer are poor environmental conditions, materials from which trailers are built, inappropriate assembly processes (incorrectly made welds, choosing screws or placing them so that they cannot withstand loads etc.), the inadequacy of the vehicle's speed to the runway quality, the detachment of the trailer from the towing hitch attached to the vehicle, lack of verification of the condition of the trailer (worn tires, the absence of the braking system, damaged of the resistance elements), the resonance of the trailer or the lack of attention of the drivers in traffic. The paper presents the experimental researches performed on a real trailer with one axle attached to a vehicle and driven on a road with and without obstacles. So, the influence of uncontrolled disturbing dynamic effects was analyzed based on acceleration signals recorded during test.

This paperwork deals with dynamics of overhead crane. Dynamically speaking, I considered the overhead crane beams as continuous medium with distributed elasticity and weight, simple supported at ends, stressed by distributed as well as focused forces. The distributed forces are the own weight and forces of inertia (mass forces) and focused forces are those produced by the carriage and transported load. Focused forces may travel along the overhead crane, so they have variable position and are, in their turn, variable in time as the carriage, always considered in contact with overhead crane, is, on one hand subject to the same accelerations as the beams oscillate in vertical plane in the place where the carriage is at the said moment, and produce variable inertia forces, and, on the other hand, a load is hanging on it, sustained by elastic cables, pulling down with a variable force, depending on how oscillations of the load and overhead crane beam mix up together. The overhead crane is a beam with variable profile subject to static and dynamic, focused and distributed loads. This makes the mathematic model of the overhead crane dynamics to be very complicated and the presentation that follows shall prove it. Analysing the results presented in this study it may come to the conclusion that monitoring and analyse of overhead crane dynamics is extremely important because it may highlight the potentially dangerous situations in operation of this equipment.

To study the formation of the solidification structure including the columnar-to-equiaxed transition (CET) under the influence of ultrasound, a 2-zone furnace system and an ultrasound equipment were utilized. The 2-zone furnace system consists of an induction furnace with a top coil and a bottom coil, a graphite crucible, and. a water-cooled chill block located at the bottom of the crucible. By controlling both the top and bottom coil output power independently, the furnace can create various temperature gradients and cooling rates in different regions of the graphite crucible. The ultrasound probe was inserted at the top of the crucible. The top of the crucible was also thermally insulated. Temperature measurements were performed at different locations in the crucible. Optical microscopy was used to characterize the microstructure of the A356 cylindrical ingots. The effects of ultrasound on the microstructure formation during solidification of A356 alloy was studied. A numerical model was developed to compute the temperature gradients and mushy zone evolution in the crucible and to assist in developing of solidification maps.

In this study, fnite time Lyapunov exponent (FTLE) fields from turbulent reacting flows are evaluated. The unsteady turbulent velocity field is obtained from large-eddy simulations, and reacting (DLR Flame A) and non-reacting unconfined jet configurations are considered. Backward FTLE analysis on the velocity field is performed, and the anal- ysis shows that the ridges approximate the flow structure associated with the organized fuid structure. To examine the merit of this method in identifying coherent structures, we compare the results with the well-known Q-criterion.

Direct Numerical Simulation (DNS) and Large-Eddy Simulation (LES) have been em- ployed for computing turbulent flows . While DNS resolves all turbulent scales involved in the dynamics with no physical modeling, LES represents the energy contained in the large scales, and effects of the smaller scales are taken into account either explicitly through a subgrid scale model or implicitly through the numerical dissipation of the nu- merical method. Besides numerical algorithms, two factors determine the quality of LES: the physical model or dissipation of the subgrid scales (SGS), which are filtered out in the governing equations, and the filter width, which describes the numerical resolution of the resolved scales.

This paper proposes an efficient and secured transmission system for personal data acquired through optical character recognition (OCR) that can be considered a viable solution for the patient data processing issue in the actual medical system. The procedure involves capturing the ID document containing the data through scanning or photography. The image is encrypted, sent to a cloud, decrypted and then processed by an OCR software in order to extract the targeted information. It has also an additional feature that allows the medical personnel to communicate with each other or grant access to specific information of a certain patient through a chat server. Advantages of the structure include the significant decrease in the amount of time, needed for submitting the personal data into the system, as well as the possibility for a medical specialist to consult with one of his homologous, to get a second opinion/expertise.

This paper presents a prototype which can locate the area of highest sun intensity and track it according to its movement. The device used to track the sun uses a light dependent resistor connected to two stepper motors, used to generate movement of the panel on both vertical and horizontal axis. The motors, connected to their drivers, together with the light dependent resistor and a potentiometer, are connected to the Arduino Uno microcontroller. The purpose of the prototype is to improve the solar panels to generate up to 60% more energy by enabling solar tracking and by ensuring the panels maintain a perpendicular angle to the sun rays. The solar tracking functions compare a defined maximum value with the data coming from the light dependent resistor and find the difference between the two values, then chooses the smallest value, which correlates to the highest sun intensity.

Adaptive user interfaces can be more effective in increasing accessibility of the interaction between people and systems, especially for elderly or people with different impairments such as cognitive impairments in people with dementia. There are two possible types of adaptation for interfaces: navigation and content-based adaptation. Both types of adaptation must be made based on the context (devices that are used) and on the user profile. This paper presents a method for interface adaptation using user classification. Users are classified based on their interactions with the interface.

This paper addresses the problem of automatic data collection for the purpose of indoor positioning via Received Signal Strength (RSS) fingerprinting. A robotic platform with basic odometer sensors was used in an university building to automate the process of data acquisition which becomes particularly time consuming when considering mapping of large spaces such as shopping malls or hospitals. More than 3000 observations were collected. We associated for each observation their two dimensional coordinates with the received MAC RSS vector. Preprocessing methods included data augmentation and feature normalization. We searched for multiple models and one of the best performance was achieved by using neural networks and post-filtering.

Computational dynamics of technological equipments dealing with intensive, shock-like and various working regimes frames the area of this research paper. A widely used type of demolition-cutting equipment supplied by hydrostatical driving system was adopted, and ordinary scenarios of equipment exploitation have been proposed in order to dignify the very short but strong transitory states deeply depending on the material characteristics and the regime parameters. Elastic, dissipative and plastic components have been considered to compose the global characteristic of the processed material interacting with cutting tool. The authors propose a simplified rheological model intended for modeling and simulation of demolished structural elements based on composite materials, like reinforced concrete. This model is very useful for simulation the variable dynamics of the interaction between the demolition-cutting equipments and the composite elements in order to evaluate the parameters evolution within the process, and obviously, to optimize driving system for minimize transitory effects and vibratory evolutions. The advantage of this computational approach results from the reduced resources involved by simulation tasks, taking into account the global evaluation of the resistant forces usually required for this kind of behavioral analysis.

This paper deals with structural damage identification at vibration isolators with elastomeric-based composite, through continuous or periodical evaluation of behavioral changes of the dynamic characteristics. It has supposed only structural damages of passive isolators, appearing inside the elastomeric core. Theoretical approaches has been provided, computer simulation scenarios regarding some potential critical cases has been developed, and experimental tests has been performed, in order to evaluate main correlation between the levels of structural integrity and the operational performance respectively. Partial results indicate an acceptable sensitivity of this dynamic method with damage detection, and establish next goal of the research in evaluation of the failure imminence and accurately localizing techniques.

Casting at low superheat has a strong influence on the solidification morphology and macro- and microstructures of cast alloys. This paper shows the microstructure and microsegregation of cast Mg AZ31B alloy at superheat of 5°C, summarizes the multiscale model, and describes the simulation results obtained with a previously developed stochastic mesoscopic solidification model capable of predicting the microstructure of the cast alloy. The simulation results are compared with casting experiments carried out using the Magnetic Suspension Melting process. Casting at this low superheat was found to produce castings with a fine globular grain structure, with an average grain size of about 80 µm, which is about one-third the size of that obtained by conventional casting techniques. The stochastic model was validated against the experimental measured grain structure and Al microsegregation. A parametric study was performed to determine some key material and process parameters related to processing of cast Mg AZ31B alloy.

This paper examines the electromagnetic and flow field modification caused by the placement of electrically conducting media in the vicinity of the coil and molten metal and the corresponding influences of coil operating frequency. The electromagnetic field characteristics were numerically calculated using the mutual inductance technique. An improved dual-zone model was employed to describe flow behavior in the mushy region, and accounts for flow damping via interactions between the crystallites and the turbulent eddies. Calculations were performed for unidirectional solidification of an Al-4.5 wt% Cu alloy in a bottom-chill mold undergoing EM stirring. It was found that the presence of shields greatly modified the Lorentz force distribution within the melt. This led to noteworthy changes in the flow directionality, as well as changes in the spatial variation of temperature as solidification progressed. It was also found that these effects were most pronounced at low frequencies. The significance of these findings with respect to solidification process design will be discussed.

There is strong evidence showing that microstructure and mechanical properties of a cast component can be considerably improved if nanoparticles are used as a reinforcement to form a metal-matrix nanocomposite. In this paper, 6061 nanocomposite castings were fabricated using the ultrasonic stirring technology (UST). The 6061 alloy and Al2O3/SiC nanoparticles were used as the matrix alloy and the reinforcement, respectively. Nanoparticles were injected into the molten metal and dispersed by ultrasonic cavitation and acoustic streaming. The applied UST parameters in the current experiments were used to validate a recently developed multiphase computational fluid dynamics (CFD) model, which was used to model the nanoparticle dispersion during UST processing. The CFD model accounts for turbulent fluid flow, heat transfer, and the complex interaction between the molten alloy and nanoparticles using the ANSYS’s fluent dense discrete phase model (DDPM). The modeling study includes the effects of ultrasonic probe location and the initial location where the nanoparticles are injected into the molten alloy. The microstructure, mechanical behavior, and mechanical properties of the cast nanocomposites have been also investigated in detail. The current experimental results showed that the tensile strength of the as-cast-reinforced 6061 alloy with Al2O3 or SiC nanoparticles increased slightly while the elongation increased significantly. The addition of the Al2O3 or SiC nanoparticles in 6061 alloy matrix changed the fracture mechanism from brittle dominated to ductile dominated.

This paper examines the role of new coil configurations on the stirring of an aluminum alloy in electromagnetic solidification processes. The model presented describing the fluid flow phenomena is based on a dual-zone description of the solidifying region, with coherency occurring at very low solid fraction, and accounts for damping of turbulence due to phase change within the control volume. Calculations were performed for Al 3104 alloy placed within a six-turn coil of various turn configurations. In comparison to previous work, it was found that the turn configurations do not have as strong of an effect as that of coil translation along the long axis of the casting. The implications with regards to solidification behavior will be discussed.

A multi-component Computational Fluid Dynamics (CFD) model developed to study macrosegregation phenomena in 65-tons 2.5 m diameter round-sided steel ingots has been verified through advanced microstructural characterization, chemical analysis and non-destructive testing. Radial and central bars machined out from the full-scale as-cast ingot were compared against the model predictions in terms of columnar-to-equiaxed transition (CET), channel segregation as well as centerline segregation within the central zone of the ingot, which are inherent in the production of industrial scale alloy ingots. The CFD model solves for volume fraction of phases, time-dependent temperature distribution, mass and species transfer to predict segregation patterns in the solidifying ingot. It addresses the influence of various process parameters and mold design aspects on solidification behavior, such as: mold system, pouring rate, superheat, hence, resulted cooling rates, thermal gradients and chemical composition variations. The numerical and experimental results were compared and discussed.

The ladle metallurgical furnace (LMF) is one of the most important secondary steel refining equipment to remove inclusions and produce clean low-sulfur steel. With the increasing demand for high desulfurization efficiency in the LMF process, it is very useful to predict the slag-steel interaction and the desulfurization behavior for providing assistance in the industrial process control. In this study, a modeling analysis tool for predicting the slag-metal reactions and desulfurization kinetics in gas-stirred ladles has been developed. The model consists of two uncoupled components: (i) a computation fluid dynamics (CFD) model for predicting fluid flow and slag-steel interface characteristics, and (ii) a multicomponent reaction kinetics model for predicting desulfurization. The slag eye behavior, slag-steel interface area, and mass transfer rates in the LMF were simulated by the CFD model. The desulfurization kinetics were predicted using the CFD simulation results together with the thermodynamic calculations. This approach is validated in terms of the evolution of the sulfur content based on industrial data. As the model can considerably decrease the computational time and cost for the analysis of the sulfur evolution during the LMF processing, it would be a very useful tool for the steel industry for quick and accurate predictions of the sulfur evolution in the ladle refining process.

A three-dimensional, transient CFD modeling approach has been developed to predict the multiphase fluid flow, slag-steel interface characteristics and inclusion removal in a gas-stirred ladle with taking the fluctuant top slag layer into account. The comparison with experimental data indicates that the model can accurately predict the slag-steel interface and slag eye characteristics. The discrete phase model was used to trace the individual inclusion movement through particle trajectory. Finally, the contribution of different removal mechanisms on the inclusion removal was investigated. The results show that the slag capture is the prevailing mechanism for inclusion removal. The bubble-inclusion attachment also helps remove a considerable amount of inclusions, while the inclusion removal ratio by wall adhesion is quite low.

A three-dimensional (3D) stochastic model for simulating the evolution of dendritic crystals during the solidification of alloys has been developed. The model includes time-dependent computations for temperature distribution, solute redistribution in the liquid and solid phases, curvature, and growth anisotropy. The current 3D simulation software was written in Fortran 90 with threading (shared memory system with multiple cores) in both native Linux and Windows threads. This 3D software is highly efficient. It can run on PCs with reasonable amount of RAM and CPU time. 3D stochastic mesoscopic simulations at the dendrite tip length scale were done to simulate the evolution of the columnar and equiaxed dendritic microstructures, columnar-to-equiaxed transition and segregation patterns during solidification of alloy 718.