Multidimensional Computer Research Articles

A shock-stable rotated-hybrid Riemann solver on rectangular and triangular grids

The rotated Riemann solver is robust against the carbuncle phenomenon, especially for multidimensional computation. Moreover, hybrid techniques are usually used to enhance the stability of an accurate scheme by combining an accurate scheme with a diffusive scheme. This paper proposes a rotated-hybrid Riemann solver named the rotated-HLLC+ scheme. The scheme is developed by hybridizing the Harten–Lax–van Leer contact (HLLC) scheme with the advection upstream splitting method based on a flux vector splitting (AUSMV+) scheme by following the rotated Riemann solver approach. The unit vector n1 is calculated from the velocity-difference vector, and the unit vector n2 is the orthogonal vector. The linearized analysis suggests that the HLLC scheme should be used in the direction of n1 and the AUSMV+ scheme in the direction n2. In this way, the hybrid scheme becomes shock-stable with less numerical dissipation. Moreover, the pressure-based method is used to detect the shock wave. Several numerical experiments suggest that the pressure cutoff parameter εp=0.01 may be generally suitable and provide a stable solution with little additional numerical dissipation. The last two numerical examples show that the computational performance of the rotated-HLLC+ scheme is comparable to the HLLC scheme for the weak shock reflection over convex double wedges. However, the scheme is approximately 9% faster than the HLLC scheme for the double Mach reflection of a strong shock wave. The proposed scheme gives fast, stable, and accurate solutions on rectangular and triangular grids.

Efficiency of PROMIS MCAT Assessments for Orthopaedic Care

ABSTRACT Administration of patient-reported outcome measures (PROs), using multidimensional computer adaptive tests (MCATs) has the potential to reduce patient burden, but the efficiency of MCAT depends on the degree to which an individual’s responses fit the psychometric properties of the assessment. Assessing patients’ symptom burden through the administration of MCATs is gaining popularity in clinical settings, especially in orthopeadics where patients reporting low physical functioning and high pain interference may not always report high levels of depression. Are MCATs more efficient and precise than unidimensional CATs in a patient profile where the person-item fit varies between symptoms? Results depend on the item selection algorithm used in the assessments. Constraining item selection algorithm can substantially reduce test lengths where person-item fit is poor. This study demonstrates how MCAT can reduce patient burden in settings where collecting PROs is becoming part of routine care. Abbreviations: PRO: Patient-reported outcome; PROMIS®: Patient-Reported Outcomes Measurement Information System; CAT: Computer Adaptive Test; IRT: item response theory; EHR: electronic health record; UCAT: unidimensional computer adaptive tests; MCAT: multidimensional computer adaptive tests; HRQOL: health-related quality of life; MEPV: minimum expected posterior variance; SE: standard error; RMSE: root mean squared error; EAP: Expected a priori; MPEV-P: minimum expected posterior variance with domain preference; KL: Kullback-Leibler.

Mathematical modeling method based on heterogeneous cellular network algorithm and computer multi-dimensional space

Due to the rapid development of services such as computer multi-dimensional space, traditional cellular networks are quantified and diversified, and it is difficult to meet the future connection needs of green network users. The heterogeneous cellular network algorithm places multiple microcells and relay nodes under the macrocell. This multi-layer network architecture can not only shorten the data transmission link, but also reduce the energy consumption of base stations and terminals. In addition, through spectrum space reuse Capability and spectrum efficiency improve the efficiency of the system, but this also increases the number of base stations and network construction costs, and significantly increases energy consumption and operating costs of operators' electricity expenditures. In addition, in order to achieve parallel transmission of data, placing multiple millimeter wave input and output antenna systems in heterogeneous network microcells can meet the high-speed data needs of indoor users, but the antenna array requires many RF links to drive, which increases the hardware implementation. Complexity, cost and energy consumption. According to the above-mentioned problems, a reconfigurable modular robot is established based on the multi-dimensional computer space. It is composed of modules with the same interface and can be assembled into different configurations according to different tasks. Compared with the original robot, the reconfigurable modular robot is more adaptable to the work and environment, and flexible. Then the basic and core technologies such as kinematics, type synthesis, scale synthesis, error and control of the reconfigurable modular robot are mathematically modeled, so as to effectively apply and promote the reconfigurable modular robot in practice, and make it has theoretical and practical value.

Benefits of using matrix methods in teach-ing mechanics in higher education institu-tions

Problem. Basic concepts, concepts, principles of mechanics are mainly taught from simple to complex in institutions of higher technical education, which to some extent resembles a course on the history of mechanics. In today's conditions, the education system is required to take into account current trends in scientific and engineering fields. The use of inherently geometric methods of vector algebra and vector analysis as a basis for studying mechanics is losing its relevance. To a certain extent, this approach interferes with the use of multidimensional spaces (configurational and phase), tensor algebra, and computer technologies in modeling complex mechanical systems. Goal. The goal is to expand the field of application of the matrix formalism to infinite-dimensional spaces, justify its advantages compared to other approaches used in teaching the basics of mechanical disciplines, and demonstrate its capabilities in solving complex practical problems, both in terms of modeling and in terms of using computer technologies. Methodology. The methodological basis for choosing matrix methods is the use of infinite-dimensional and abstract, in physical terms, spaces when studying the movement of mechanical systems. The fundamental impossibility of accurately describing the state of a mechanical system requires the use of statistical modeling methods and the extension of the so-called law of conservation of matter in the form of a balance equation to these models. Results. It is shown that the matrix method, which is widely used in quantum mechanics and very limited in classical mechanics, allows you to use the advantages of the transition to phase space when obtaining canonical equations and when solving problems of kinematics and dynamics of a solid body. Originality. The paper proposes certain improvements of the matrix apparatus, related to the use of geometric parameters of the mechanical system as indexes. That is, infinite-dimensional matrices with real coefficients are used. Practical value. The proposed method allows you to effectively solve the problems of the mechanics of an absolutely rigid body without using any theorems of the general course, remaining within the limits of standard mathematical training.

Multidimensional cerebellar computations for flexible kinematic control of movements

Both the environment and our body keep changing dynamically. Hence, ensuring movement precision requires adaptation to multiple demands occurring simultaneously. Here we show that the cerebellum performs the necessary multi-dimensional computations for the flexible control of different movement parameters depending on the prevailing context. This conclusion is based on the identification of a manifold-like activity in both mossy fibers (MFs, network input) and Purkinje cells (PCs, output), recorded from monkeys performing a saccade task. Unlike MFs, the PC manifolds developed selective representations of individual movement parameters. Error feedback-driven climbing fiber input modulated the PC manifolds to predict specific, error type-dependent changes in subsequent actions. Furthermore, a feed-forward network model that simulated MF-to-PC transformations revealed that amplification and restructuring of the lesser variability in the MF activity is a pivotal circuit mechanism. Therefore, the flexible control of movements by the cerebellum crucially depends on its capacity for multi-dimensional computations.

Self-propelled cellular translocation of Janus-shaped graphene quantum dots: A molecular dynamics simulation and thermodynamic analysis

Although spatially heterogeneous oxidation is pivotal to the cellular translocation process of graphene quantum dots (GQDs), the dynamical road to the thermodynamically stable translocation conformation remains hazy. In this study, we illuminate the bio-interface doctrine involving the cellular translocation of Janus-shaped oxidized GQDs by performing multi-dimensional pathway computations predicated on coupled microsecond-long molecular dynamics and well-tempered metadynamics simulations. The oxidation nanodomains of Janus-shaped GQDs spontaneously yield hydrogen-bonds with polar lipid heads, while their pristine graphene nanodomains hydrophobically associate with nonpolar lipid tails, and thus respond as self-propelled nanomotors across biological membranes. Hydrophobic-associations and hydrogen-bondings are found to be competitively coordinated, which dictates the dynamic pathway and thermodynamic states for cellular translocation, particularly modulating the adaptive self-propelling activity. The translocational phase diagram is drawn, demonstrating that GQDs with moderately square-patterned oxidation and thin thickness facilitate excellent translocation and minimal biological nanotoxicity. Importantly, intermolecular mechanochemistry is discovered to play a crucial role in energy transduction and nanomechanical interactions, which in turn affect the spatial rotation pathways of GQDs, as well as the membrane perturbations. Overall, this study provides an intuitive insight into the dynamics and thermodynamics of spontaneously translocating GQDs, opening up brand-new avenues for developing GQD-enabled nanocarriers or antibiotics.

HOMOGENEOUS PLANS OF MULTI-FACTORY EXPERIMENTS ON QUASI-RANDOM R-ROBERTS SEQUENCES FOR SURROGATE MODELING IN A VORTEX STYLE STRUCTUROSCOPY

Context. The article is devoted to the creation of multifactorial experimental plans based on quasi-random recursive Roberts Rsequences. The object of the research is the process of creating computer-aided experimental design plans. The aim of the article is to create multifactorial, namely six- and seven-factor, uniform plans of experiments with low discrepancies, study of their projection properties and demonstrate their use on the example of surrogate modeling in eddy current structuroscopy.
 Method. An iterative method of unit hypercube even filling with reference points was used for constructing multidimensional experimental plans. It provides acceptable indicators of homogeneity and is realized on the basis of quasi-random nonparametric additive recursive Roberts R-sequences using irrational numbers, which, in turn, are obtained on the basis of the generalized Fibonacci sequence. The criterion for plans perfection is the assessment of homogeneity in terms of differences invariant with respect to the rotation of coordinates and re-marking and ordering of factors and which quantitatively characterize the deviation of the generated distribution from the ideal uniform.
 Results. Six- and seven-factor computer uniform experimental plans have been created for cataloging, which are characterized by low discrepancies and sufficiently high-quality projection properties. The tendency, which had been previously proved in the authors' research, for preserving these experimental plans characteristics in multidimensional factor spaces, which is observed with increasing number of plan points, has been confirmed. The evaluation of the quality of the created experimental plans is carried out both by visual analysis of the scattering matrix of all two-dimensional projections and by quantitative indicators of heterogeneity of the set of vectors that form the plan, namely centered and cyclic discrepancies.
 The example of the initial stage of creating a surrogate model to solve the problem of identifying profiles of electrophysical parameters in eddy current structuroscopy shows certain features of the application for created plans, in particular the transition from the plan for a unit hypercube to the plan in real factor space in the form of a hyperparallelepiped, which does not significantly affect its characteristics of homogeneity of the distribution of points.
 Conclusions. For the first time, the problem of creating six- and seven-factor uniform plans of experiments with low rates of centered and cyclic discrepancies based on R-sequences of Roberts was solved. The projection properties of the created experimental plans for different number of points were investigated. The method of constructing multidimensional computer plans of experiments taking into account the peculiarities of eddy current structuroscopy was improved. The use of six-dimensional experimental plans on the example of surrogate modeling in eddy current structuroscopy was demonstrated. The results of the study can be used in the construction of surrogate mathematical models of physical processes by any known methods of approximation.

A Multi-Dimensional and Multi-Factor Trust Computation Framework for Cloud Services

In this paper, we propose a novel trust computation framework (TCF) for cloud services. Trust is computed by taking into consideration multi-dimensional quality of service (QoS) evidence and user feedback. Feedback provides ample evidence regarding the quality of experience (QoE) of cloud service users. However, in some cases, users may behave maliciously and report false feedback. Users can carry out collusion and Sybil attacks to slander/self-promote cloud services. Trust computed in such cases could be misleading and inaccurate. Evaluating the credibility of user feedback can help in not only preventing the collusion and Sybil attacks but also remunerating the affected cloud services. Despite the advantages of credibility evaluation, very few studies take into consideration feedback credibility and multi-dimensional evaluation criteria. Considering the limitations of existing studies, we propose a new TCF in which trust is computed by aggregating multi-dimensional evidence from QoS and QoE. We have used multi-dimensional QoS attributes to compute the objective trust of cloud services. The QoS attributes are divided into three dimensions, i.e., node profile, average resource consumption, and performance. The node profile of a cloud service is attributed to CPU frequency, memory size, and hard disk capacity. The average resource consumption is quantified based on the current CPU utilisation rate, current memory utilisation rate, current hard disk utilisation rate, and energy consumption. Moreover, the performance of a cloud service is measured by the average response time and task success ratio. Besides that, the credibility of feedback is evaluated to prevent the malicious behaviour of cloud users. Our results demonstrate the effectiveness of our proposed TCF in computing accurate trust in cloud services.

Ontology of functional synergetics in virtual cognitive-semiotic design of information processes and systems

Objectives . In view of the currently expanding practice of applying methods for configuring ontologies of designing information processes and systems, information technology (IT) specialists need to disclose the definition of such a new concept as functional synergetics. This concept is actualized by the course of development of virtual information technologies, forming the system foundation for methods of design ontologies and indicating attributes for the correct formation of design ontologies of relevant dynamic information processes and systems. In the present work, this is done by means of analytical review. Methods . The analytical review is based on the authors’ vision of deepening the concept of synergetics as applied to a variety of modern information processes and systems. This context concessionally conjugates the combined use and consideration of such approaches as the method of ontologies (the major component of the resulting concession of methods), methods of cognitive semiotics, autopoiesis, and other manifestations of synergetics with related methods and techniques of emergent evaluation of the role and effectiveness of any occurring systemic changes. It is this combined dynamics of information processes and systems that allows the authors to put forward a developing treatment of the methods of synergetics as functional. Results . The concept of functional synergetics was clarified and deepened based on the method of ontologies. In the theory of information processes and systems, it is manifested in updating ontologies accompanying scientific and engineering projects that use synergetics as an initial methodological basis. It turns out that the functional features of synergetics in the context of assessments and functional ordering of modern IT devices give it new opportunities in highlighting the significant indicators of system changes: properties, attributes, and manifestations of functionalsynergistic nature. It is these three concepts, revealed by synergetics as a functional eyepiece, that distinguish functional synergetics from the generally accepted definition of synergetics as such. Matching form to content, autopoiesis, development, and transformations occurring with informational processes and systems with their emergent consequences are the essence and feature of functional synergetics. Tracing what is happening in dynamics, in the inseparability of assessments and regulations of the set of properties, attributes, and manifestations of the analyzed processes to an even greater extent clarifies the essence and role of the concept introduced by the authors in the general classical theory of information processes and systems. In the related analysis, virtual reality, augmented reality, mixed reality, expanded reality, composite reality, coupled reality, geoinformation systems, multidimensional computer graphics, fractal graphics, holographic graphics, computer teletype games, X-reality, etc., which have essential dynamic characteristics and properties, are included here as objects of research and design. Conclusions . Improvement of the theory and practice of creating and using information processes and systems from the position of recognizingthe accelerating speed and dynamics of how their properties and indicators are modified leads the synergistic methodology of assessments and control mechanisms to the emergence of a clarifying concept of functional synergy. This is a complex and dynamic concept, which includes its interpretation of the positions of classical synergetics and related paradigms of cognitive semiotics, etc. The method of ontologies, which is gaining more and more popularity, is the main means and tool of such unification. When combined with cognitive semiotics, functional synergetics becomes a powerful science-intensive tool for further development of the theory and practice of modern multimedia intensified information systems and their information fields described by both imperative and convivial paradigms.

Two-Dimensional Simulations of Laser Shock Peening of Aluminum With Water Confinement

Nowadays, advanced surface improvement techniques are required, due to continuously rising demands in aerospace and automotive productions. Laser shock peening (LSP) is a widely known modern surface enhancement method. LSP usually deals with nanosecond laser pulses with high intensities exceeding 1 GW/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . Due to very short time scales, all the occurring physical phenomena and processing parameters are extremely difficult to measure and study just based on experimental investigations. Therefore, multidimensional computer simulations of the processes within LSP are required for further optimization. In this work, a 2-D hydrodynamic simulation of water-confined nanosecond laser shock peening of an aluminum target is performed applying the open-source code MULTI2D. Circular laser beam with a pulse energy of 1 J, 20-ns duration, a diameter of 1 mm, and a uniform spatial distribution is used. Spatial profiles of the laser-induced plasma pressure and temperature are determined together with the shock wave parameters. It is shown that the plasma is highly confined and a temperature-affected region is very thin. Radial expansion of the surface pressure profile and the shock wave propagation can be observed, indicating that radial effects have to be considered during the industrial application of LSP. The obtained results are in good agreement with available simulations and measurements, validating the proposed simulation approach. In addition, temporal and spatial distributions of the pressure at the surface of the target material can be applied in finite-element simulations to predict residual stresses distributions.

Multidimensional Computer Interconnection Networks with the Virtual Cut–Through Routing

A theoretical model of an n-dimensional toroidal interconnection network with the virtual cut-through routing is developed. The network performance is characterized as a function of the message load for various values of the network and communication parameters. An exact analytical expression for the saturation point has been obtained. The method of statistical physics known as the mean field theory approximation has been used in order to derive analytical expressions of latency as a function of message generation rate for the full range of the network load. The saturation point has been found proportional to the number of the torus dimensions and inversely proportional to the message length and to the length of the path from the source to the destination. It was found that the transition to the saturation state is a second-order (continuous) phase transition with a critical exponent equal to 1.

Eu's generalized hydrodynamics with its derived constitutive model: Comparison to Grad's method and linear stability analysis

Recently, the generalized hydrodynamic equations (GHE) and nonlinear coupled constitutive relation (NCCR) model have been successfully utilized for the practical application in stable numerical computations of the non-equilibrium flows. However, their stability property has never been studied theoretically, and the inherent connection with classical Grad's moment still remains unclear. In order to clarify these issues, Eu's method, including the modeling of the non-equilibrium distribution function and the cumulant expansion for collision terms, is revisited to derive the modified moment system. A comparison of Eu's moment method with existing Grad's is presented in detail from the perspectives of distribution function and closure theory. The original infinite system of Eu's distribution function is first truncated into a finite system with 13 moments. Then through our attempt of Taylor expanding the truncated distribution function, a connection between Eu's distribution and Maxwellian and Grad's is established. Subsequently, a truncated closure method is conducted to clarify the relation between Eu's moment and Grad's moment equations. Finally, linear stability analysis of GHE and NCCR model is performed in one-dimensional and multi-dimensional processes, which shows that the equations are unconditionally stable for all wavenumbers and frequencies in the equilibrium rest state (ui0=0) and uniform-moving state (ui0≠0). The linear stability of GHE and NCCR model assures their numerical stability in the multi-dimensional computations, which can be deemed as one of the major benefits of Eu's theory.

A Massive Image Recognition Algorithm Based on Attribute Modelling and Knowledge Acquisition

In this paper, an in-depth study and analysis of attribute modelling and knowledge acquisition of massive images are conducted using image recognition. For the complexity of association relationships between attributes of incomplete data, a single-output subnetwork modelling method for incomplete data is proposed to build a neural network model with each missing attribute as output alone and other attributes as input in turn, and the network structure can deeply portray the association relationships between each attribute and other attributes. To address the problem of incomplete model inputs due to the presence of missing values, we propose to treat and describe the missing values as system-level variables and realize the alternate update of network parameters and dynamic filling of missing values through iterative learning among subnets. The method can effectively utilize the information of all the present attribute values in incomplete data, and the obtained subnetwork population model is a fit to the attribute association relationships implied by all the present attribute values in incomplete data. The strengths and weaknesses of existing image semantic modelling algorithms are analysed. To reduce the workload of manually labelling data, this paper proposes the use of a streaming learning algorithm to automatically pass image-level semantic labels to pixel regions of an image, where the algorithm does not need to rely on external detectors and a priori knowledge of the dataset. Then, an efficient deep neural network mapping algorithm is designed and implemented for the microprocessing architecture and software programming framework of this edge processor, and a layout scheme is proposed to place the input feature maps outside the kernel DDR and the reordered convolutional kernel matrices inside the kernel storage body and to design corresponding efficient vectorization algorithms for the multidimensional matrix convolution computation, multidimensional pooling computation, local linear normalization, etc., which exist in the deep convolutional neural network model. The efficient vectorized mapping scheme is designed for the multidimensional matrix convolution computation, multidimensional pooling computation, local linear normalization, etc. in the deep convolutional neural network model so that the utilization of MAC components in the core loop can reach 100%.

Applying Evidence‐Centered Design in the Development of a Multidimensional Adaptive Reading Motivation Measure

AbstractAdaptive tests are more efficient than fixed‐length tests through the use of item response theory; adaptive tests also present students questions that are tailored to their proficiency level. Although the adaptive algorithm is straightforward, developing a multidimensional computer adaptive test (MCAT) measure is complex. Evidence‐centered design (ECD) can provide a highly structured framework to guide the development of a MCAT. In this paper, the development of the adaptive reading motivation measure (ARMM) demonstrates the process of applying ECD to the development of a MCAT measure. This paper focuses on the conceptual assessment framework layer of the ECD that guides the technical aspects of MCAT development. The five models of conceptual assessment framework layer are student model, task model, evidence model, assembly model, and presentation model. How each model guided the development of the ARMM is described in detail. In this paper, we demonstrate how the conceptual assessment framework in ECD can provide a useful structure for developing MCAT measures.

СИНТЕЗ ВИХРОСТРУМОВИХ ПЕРЕТВОРЮВАЧІВ З ОБ’ЄМНОЮ СТРУКТУРОЮ СИСТЕМИ ЗБУДЖЕННЯ, ЩО РЕАЛІЗУЄ ОДНОРІДНУ ЧУТЛИВІСТЬ В ЗОНІ КОНТРОЛЮ

A method for nonlinear surrogate synthesis of surface eddy current probes with a volumetric structure of the excitation system was proposed. This method a priori provides a given uniform distribution of eddy current density in the testing object area where the measuring coil is located. The implementation of the task using modern metaeuristic stochastic algorithms for finding the global extremum was achieved. For the effective usage of such algorithms, taking into account the effect of velocity, metamodels of eddy current probe were preliminarily created. They were built using a productive approximation technique based on artificial radial-basis neural networks with a Gaussian activation function. Acceptable accuracy of metamodels was achieved due to the simultaneous application of the search area decomposition technologies and plural neural networks based on the techniques of associative machines with group methods for obtaining a solution. For metamodels creation a multidimensional computer experiment design with high homogeneity was used on the basis of the parameterless additive Rd-Kronecker sequence. Numerical experiments to determine the eddy current density distributions which formed by synthesized excitation structures were carried out. The advantages of using a three-dimensional structure excitation system in comparison with classical and planar ones in terms of increasing the width of the testing zone, which is characterized by uniform sensitivity, were shown. Examples of practical implementation of an excitation system with a volumetric structure for an surface eddy current probe are given. References 13, figures 8, table 1.

Improving the Delivery of Function-Directed Care During Acute Hospitalizations: Methods to Develop and Validate the Functional Assessment in Acute Care Multidimensional Computerized Adaptive Test (FAMCAT)

Objective:To (1) develop a patient-reported, multidomain functional assessment tool focused on medically ill patients in acute care settings; (2) characterize the measure's psychometric performance; and (3) establish clinically actionable score strata that link to easily implemented mobility preservation plans. Design:This article describes the approach that our team pursued to develop and characterize this tool, the Functional Assessment in Acute Care Multidimensional Computer Adaptive Test (FAMCAT). Development involved a multistep process that included (1) expanding and refining existing item banks to optimize their salience for hospitalized patients; (2) administering candidate items to a calibration cohort; (3) estimating multidimensional item response theory models; (4) calibrating the item banks; (5) evaluating potential multidimensional computerized adaptive testing (MCAT) enhancements; (6) parameterizing the MCAT; (7) administering it to patients in a validation cohort; and (8) estimating its predictive and psychometric characteristics. Setting:A large (2000-bed) Midwestern Medical Center. Participants:The overall sample included 4495 adults (2341 in a calibration cohort, 2154 in a validation cohort) who were admitted either to medical services with at least 1 chronic condition or to surgical/medical services if they required readmission after a hospitalization for surgery (N=4495). Intervention:Not applicable. Main Outcome Measures:Not applicable. Results:The FAMCAT is an instrument designed to permit the efficient, precise, low-burden, multidomain functional assessment of hospitalized patients. We tried to optimize the FAMCAT's efficiency and precision, as well as its ability to perform multiple assessments during a hospital stay, by applying cutting edge methods such as the adaptive measure of change (AMC), differential item functioning computerized adaptive testing, and integration of collateral test-taking information, particularly item response times. Evaluation of these candidate methods suggested that all may enhance MCAT performance, but none were integrated into initial MCAT parameterization. Conclusions:The FAMCAT has the potential to address a longstanding need for structured, frequent, and accurate functional assessment among patients hospitalized with medical diagnoses and complications of surgery.

Reduced mechanism for flames of propane, n‐butane, and their mixtures for application to burners: Development and validation

AbstractPropane, n‐butane, and their mixtures are commonly used as fuels for various applications. Reliable numerical simulations of flames involving these fuels are most essential to study their efficient use in domestic and industrial burners. Such simulations require a suitable reaction mechanism containing the necessary kinetics to predict key combustion characteristics in flames accurately. However, the use of detailed kinetic mechanisms for these computations is formidable in multidimensional simulations, owing to their large sizes. To address this, in this work, a compact mechanism (45 species, 392 reactions) for propane, n‐butane, and their mixtures, suitable for multidimensional simulations is derived and comprehensively validated against available experimental data in flames. The main oxidation pathways retained in this compact model are showcased. One‐dimensional (1D) computations of premixed and nonpremixed flames are carried out using FlameMaster and Chemkin‐Pro. Two‐dimensional (2D) calculations are performed within ANSYS‐FLUENT. Here, multicomponent diffusion, thermal diffusion, and radiation submodels are used. Laminar flame speeds, extinction strain rates, and amounts of major species in premixed flat flames are validated using 1D computations. Temperature and major species in propane and n‐butane jet diffusion flames are verified in 2D simulations. Further, 2D computations using the compact mechanism also predict the laminar burning velocity of premixed flames of n‐butane and propane mixtures established over a Bunsen burner. The ability of the compact mechanism to predict desired targets in premixed and nonpremixed flames is analyzed from a kinetic basis. Validation using 2D simulations demonstrates the usability of the compact mechanism in multidimensional computations.

Computer Three-Dimensional and Multidimensional Education Mode of Ideological and Political Work in Colleges Applied Research in Innovation

Research on the application of computer three-dimensional and multi-dimensional in the innovation of ideological and political education mode in universities is a necessary subject for the development of ideological and political education in universities. In terms of developing ideological and political education, some colleges and universities are not doing very well. We have the responsibility and obligation to make ideological and political education bloom in every place on campus. Therefore, we need to cut off the innovation of the three-dimensional and multi-dimensional computer education model of ideological and political work in colleges and universities to allow the ideological and political education to develop well. This is the ultimate goal of ideological and political education. This article discusses some methods of the analysis of ideological and political education and the three-dimensional computer in the innovation of ideological and political education mode in colleges and universities.

PERSONALIZED CHOICE OF STRUCTURAL MATERIALS FOR ARTIFICIAL CROWNS FROM THE LEVEL OF MULTI-UNIT ABUTMENT OR TITANIUM PLATFORM FOR DIRECT PROSTHETICS ON DENTAL IMPLANTS

The high prevalence of secondary adentia in the adult population, as well as increased aesthetic requirements of patients has contributed to the development of orthopedic dentistry. Direct prosthetics on dental implants have been increasingly used for replacing defects in the dentition. However, the choice of structural materials for dental implant-supported prostheses is not fully understood. Hence, it remains a debatable issue.&#x0D; Purpose of the study: to justify the optimal structural materials for artificial crowns from the level of a multi-unit abutment or a standard titanium platform for direct prosthetics on dental implants with the use of finite-element analysis of the stress-strain state of the “bone tissue-dental implant-abutment-suprastructure” multidimensional model under the conditions of simulation modeling.&#x0D; Materials and methods. Specialized CAD / CAE software was employed to develop multi-dimensional computer models of biomechanical systems such as “bone tissue-dental implant-abutment-suprastructure” with simulation of direct prostheses on dental implants with the corresponding physical and mechanical properties of structural elements and load conditions. The created 10 simulation models were based on combinations of two types of abutment (standard titanium platform (A1) and multi-unit abutment (A2)), and five structural materials of the crown, including lithium disilicate glass ceramic (KM1), polymer-infiltrated hybrid ceramic (KM2), polymethyl methacrylate (PMMA) (KM3), zirconia (KM4), and multi-layer zirconia (KM5)). The stress-strain state and the bearing capacity of biomechanical systems were assessed with the use of the von Mises stresses analysis and safety factors.&#x0D; Results. During a numerical experiment, there was revealed a complex stress-strain state in “bone tissue - dental implant - abutment - suprastructure” biomechanical systems. The maximum loads were recorded in systems with A1 and A2 type of abutment in the crown models (149.37 MPa and 142.08 MPa, respectively), spongy (4.25 MPa and 4.08 MPa) and the cortical bone (20.58 MPa and 20.61 MPa). The nature of the distribution of the von Mises stresses in the structural elements of systems with A1 and A2 types of abutments was found to be similar for all models under consideration with KM1, KM2, KM4, KM5 structural materials of crowns, except for the system with KM3 suprastructure material.&#x0D; Conclusions. Based on the findings of computer simulation of the stress-strain state of “bone tissue - dental implant - abutment - suprastructure” biomechanical systems, there have been grounded the optimal structural materials for dental implant-supported crowns for direct prosthetics by such abutment as a standard titanium platform and multi-unit abutment. The obtained values of the von Mises stresses analysis and safety factors showed that with external force applied to the dental implant-supported crown the at an angle of 11.5°, the greatest bearing capacity was ensured by biomechanical systems with a standard titanium platform and multi-unit abutment with crown materials including zirconia (safety factors 6.22 and 6.42 respectively), multilayer zirconia (safety factors 5.52 and 5.70) and lithium disilicate glass ceramic (safety factors 2.39 and 2.52).

Объектно-ориентированный подход к разработке моделей данных

The modern understanding of the object-oriented approach focuses on one of the main problems of programming – its automation. Many important and practically useful results have been achieved in this direction. Methods for creating object libraries and programming technologies have been developed, which greatly facilitate software development. This is especially evident in the development of WEB-applications. MVC technology has improved the efficiency of developing programs that link remote databases to client applications. However, this and similar technologies have one significant drawback, which is manifested in the fact that the time of obtaining data from their database often does not meet the requirements of both the developer and the user. For a long time, there have been ongoing discussions on this topic on the Internet. Various methods are proposed to speed up database calls, which, as a rule, complicate programming and are artificial methods that go beyond the basic technology, which are applicable to solving particular problems and require significant processing in each specific case. The article assumes that the reason for these problems lies in the fact that in the programming community there is a solidified opinion, the essence of which is that the relational data model, which serves as the basis for most modern DBMS, has nothing to do with the object-oriented paradigm. Therefore, developers of programming technologies use an intermediate technology called object-relational mapping (ORM), which, in their opinion, should connect the non-object database and the object program that provides the client application with the database. In fact, any way you organize your database systems is in the object-oriented paradigm. Based on these premises, the article discusses the object method of developing data models. For this purpose, the properties of data models are formulated, which are necessary for them to be object and to ensure high performance of programs that implement data processing on their basis. The concept of an abstract algebraic machine is introduced, which is a two-base algebraic system. Examples are given that illustrate the use of an abstract algebraic machine for solving various problems. The possibility is considered and a method is proposed for constructing algebraic systems for complex data structures, namely, tuples, which can be considered as elements of such data aggregates as multidimensional matrices, relations, files. In conclusion, it is concluded that the proposed approach allows one to prove the correspondence of various data models, which, in turn, makes it possible to effectively implement parallel processing of various databases on software and hardware complexes, the architecture of which is based on a multidimensional matrix computation model.