Universal Simulation Research Articles

Universal simulation model of the flow of ships to the sea cargo front of the port

The article describes the results of completed research aimed at clarifying the primary base of methods for technological design of ports and terminals. Along with the main parameter expected annual cargo traffic, the key for all such calculations is the structure of the ship traffic that implements this cargo flow, or the flow of the fleet of ships that sell cargo traffic. Each type of vessel is characterized by its own parameters, which determine the duration of service in the port and, ultimately, the occupancy of berths. Traditional analytical methods, without disputing the randomness of the nature of all initial and intermediate values, prescribe the use of average values for the assessment of final technological resources, correcting the results obtained by coefficients of engineering ignorance. This assumption, which makes it possible to use simple algebraic methods for working with deterministic quantities, excludes the emergence of any means of estimating the possible dispersion of values around the obtained average values. In the practice of investmentintensive facilities, such as seaports, the degree of dispersion of parameters characterizes the probability of errors of the first and second types: the creation of insufficient capacity, leading to losses from waiting in the queue for service, and the creation of excess capacity associated with the loss of excess capitalization. There is no objective measure that determines the balance between these losses, since the decision is purely entrepreneurial, based on the risk of losses and possible gains. This study describes a tool that allows you to make appropriate entrepreneurial decisions fairly objectively.

Stabilizer Tensor Networks: Universal Quantum Simulator on a Basis of Stabilizer States.

Efficient simulation of quantum computers relies on understanding and exploiting the properties of quantum states. This is the case for methods such as tensor networks, based on entanglement, and the tableau formalism, which represents stabilizer states. In this Letter, we integrate these two approaches to present a generalization of the tableau formalism used for Clifford circuit simulation. We explicitly prove how to update our formalism with Clifford gates, non-Clifford gates, and measurements, enabling universal circuit simulation. We also discuss how the framework allows for efficient simulation of more states, raising some interesting questions on the representation power of tensor networks and the quantum properties of resources such as entanglement and magic, and support our claims with simulations.

Virtual Reality Application for the Safety Improvement of Intralogistics Systems

Immersive technologies from the spectrum of Industry 4.0, such as Virtual Reality (VR), are increasingly used in research and safety analysis in industrial and intralogistics systems, including distribution warehouses and production plants. Safety in intralogistics systems is influenced by design and management processes, human behavior, and device performance. In all these areas, VR can serve as a supportive technology for visualization, testing, and employee training. However, this requires the development of principles for integrating VR into standard procedures for the design, modernization, and analysis of intralogistics and production systems. This article discusses the use of VR to analyze the occupational and functional safety of intralogistics systems. It reviews the literature and VR implementations aimed at examining and improving safety in industrial systems. The article explores the integration of VR into the design and analysis procedures for intralogistics and production systems. The authors present a five-dimensional decision space for assessing the use of VR, including identifying subjects of safety analysis, threats and hazards specific to intralogistics, countermeasures for these threats, factors affecting safety, and mechanisms by which VR can improve safety in intralogistics systems. As a subsequent step, the authors discuss using universal simulation environments that support VR technology to study and enhance safety in intralogistics systems, providing a framework example based on the FlexSim (2023 update 2) environment. Finally, this article addresses the threats and limitations of VR technology, along with the challenges and future prospects of VR in the context of Industry 4.0. The article concludes that VR can be an essential tool for increasing safety in the future, albeit with some reservations about certain features of this technology.

Universal simulation of absorption effects for X-ray diffraction in reflection geometry.

Analytical calculations of absorption corrections for X-ray powder diffraction experiments on non-ideal samples with surface roughness, porosity or absorption contrasts from multiple phases require complex mathematical models to represent their material distribution. In a computational approach to this problem, a practicable ray-tracing algorithm is formulated which is capable of simulating angle-dependent absorption corrections in reflection geometry for any given rasterized sample model. Single or multiphase systems with arbitrary surface roughness, porosity and spatial distribution of the phases in any combination can be modeled on a voxel grid by assigning respective values to each voxel. The absorption corrections are calculated by tracing the attenuation of X-rays along their individual paths via a modified shear-warp algorithm. The algorithm is presented in detail and the results of simulated absorption corrections on samples with various surface modulations are discussed in the context of published experimental results.

A universal simulation model of the continuous pipe rolling process on a controllably movable mandrel.

To study the technological process of rolling solid and hollow round profiles, it is important to have a correct mathematical description of the patterns that determine the boundaries of the deformation zone. The article analyzed scientific works that examine the calculation of geometric parameters of the deformation zone during the rolling of solid and hollow round profiles in two-roll and multi-roll calibers. As a result of the analysis, a conclusion was drawn regarding the necessity of a more detailed description of the determination patterns for the geometric boundary conditions of the deformation zone. This led to the proposal of a universal method for determining the shape of the billet and the shape of the caliber groove, as well as the derivation of the equations for the roll surface and the boundary of the contact surface of the deformation zone for various rolling schemes. The developed method allows for an increase in the accuracy of calculating the energy-force parameters of the rolling processes, including continuous rolling, in the production of solid and hollow round profiles according to the circular–oval scheme in calibers formed by any number of rolls, thanks to the consideration of a sufficiently wide range of geometric features

Application of digital twins for simulation based tailoring of laser induced graphene

In the era of man–machine interfaces, digital twins stand as a key technology, offering virtual representations of real-world objects, processes, and systems through computational models. They enable novel ways of interacting with, comprehending, and manipulating real-world entities within a virtual realm. The real implementation of graphene-based sensors and electronic devices remains challenging due to the integration complexities of high-quality graphene materials with existing manufacturing processes. To address this, scalable techniques for the in-situ fabrication of graphene-like materials are essential. One promising method involves using a CO2 laser to convert polyimide into graphene. Optimizing this graphitization process is hindered by complex parameter interactions and nonlinear terms. This article explores how these digital replicas can enhance the fabrication of laser-induced graphene (LIG) through laser simulation and machine learning methods to enable rapid single-step LIG patterning. This approach aims to create a universal simulation for all CO2 lasers, calculating optical energy flux and utilizing machine learning to control and predict LIG conductivity (ability to conduct current), morphology, and electrical resistance. The proposed procedure, integrating digital twins in the LIG production process, will avoid or reduce the preliminary tests required to determine the proper laser parameters to reach the desired LIG characteristics. Accordingly, this approach will reduce the time and costs associated with these tests and thus increase the efficiency and optimize the procedure.

A universal parallel simulation framework for energy pipeline networks on high-performance computers

Energy distribution networks represent crucial infrastructures for modern society, and various simulation tools have been widely used by energy suppliers to manage these intricate networks. However, simulation calculations include a large number of fluid control equations, and computational overhead limits the performance of simulation software. This paper proposes a universal parallel simulation framework for energy pipeline networks that takes advantages of data parallelism and computational independence between network elements. A non-pipe model of an energy supply network is optimized, and the input and output of the network model in the proposed framework are modified, which can reduce the development burden during the numerical computations of the pipeline network and weaken the computational correlation between different simulated components. In addition, independent computations can be performed concurrently through periodic data exchange procedures between component instances, improving the parallelism and efficiency of simulation computations. Further, a parallel water pipelines network simulation computing paradigm based on a heterogeneous computer hardware architecture is used to evaluate the proposed framework’s performance. A series of tests are conducted to verify the accuracy of the proposed framework, and simulation errors of less than 5% are achieved. The results of multi-threaded simulation experiments have demonstrated the feasibility of the proposed framework in a parallel computing approach. Moreover, an Advanced Micro Devices (AMD) Deep Computing Unit (DCU)-parallel program is implemented into a water supply network simulation system; the computational efficiency of this system is compared with that of its serial counterpart. The experimental results show that the proposed framework is appropriate for high-performance computer architectures, and the 18x speed-up ratio demonstrates that the parallel program based on the proposed universal framework outperforms the serial program. That provides the basis for the application of pipe network simulation on high-performance computers.

Quasi-3D Numerical Thermal Modelling of Electronic Systems in Package

The technology of three-dimensional (3D) packaging currently provides an increase in the efficiency of various electronic systems, bringing the volume of the package and heat dissipation into proper correlation. For many types of modern 3D packages the electro-thermal properties were not yet investigated. So the thermal modelling of 3D system in package (SiP) constructions became obliged for package designers. The commercial universal fully-3D simulators are not effective for practical engineers because of the complexity in using. The problem-oriented method called “Quasi-3D”was proposed and software tool Quasi-3D-Overheatwas developed to save the pre- and post-processing labour and CPU time. Numerical thermal modelling for different types of modern SiP structures: bridge-chip; p2 Pack; chip stack with TSV; embedded silicon fan-out was carried out and compared with measured temperatures. Simulation error was not more than 10–15%.

Nuevos tiempos, nuevos sistemas para el aprendizaje de la cirugía

The evolution from the traditional surgical tékhne to the current technological surgery is analyzed and the problems raised in this transition are specified. The educational methodology in surgery, the origin of the current surgical training programs of excellence, the problems that arise for learning new technologies, as well as the learning modalities based on simulation and virtual reality are presented. It is concluded that of all available methods, simulation is the current valid way of learning and that it is necessary to establish universal simulation programs in surgical training plans.

Transfer learning-based multiple digital twin-assisted intelligent mechanical fault diagnosis

With the advancement of complex system diagnosis, prediction, and health management technologies, digital twin technology has become a prominent research area in the fields of intelligent manufacturing and system operation and maintenance. However, due to the high complexity of practical systems, the difficulty of data acquisition, and the low accuracy of modeling techniques, current digital twin modeling suffers from low accuracy, and the generalization ability of models is poor when applied in model transfer. To address this issue, a novel fault diagnosis method is proposed, which integrates a digital twin model based on transfer learning. The framework introduces an innovative approach to construct multiple digital twin models using both mechanistic and data-driven models. The mechanism twin constructs a universal simulation model based on physical equipment and updates it with system response measurement data. The data twin consists of a high-dimensional fully connected-generative adversarial network twin for extracting deep features from data and an long- and short-term memory twin for extracting time series features. Subsequently, transfer learning is introduced to achieve deep fusion in the multiple digital twins system. The mechanism twin is used to obtain source domain samples to construct a diagnostic network, and the data twin is used to extract target domain features to correct the diagnostic network, thereby improving the accuracy and reliability of fault diagnosis. Finally, the proposed framework is applied to the fault diagnosis of triplex pump equipment. The accuracy of diagnosis continuously improves as the system is updated and ultimately reaches 89.28%, demonstrating the effectiveness of the algorithm and providing a novel solution for the generalization limitations of current digital twin models.

Multimaterial fiber as a physical simulator of a capillary instability

Capillary breakup of cores is an exclusive approach to fabricating fiber-integrated optoelectronics and photonics. A physical understanding of this fluid-dynamic process is necessary for yielding the desired solid-state fiber-embedded multimaterial architectures by design rather than by exploratory search. We discover that the nonlinearly complex and, at times, even chaotic capillary breakup of multimaterial fiber cores becomes predictable when the fiber is exposed to the spatiotemporal temperature profile, imposing a viscosity modulation comparable to the breakup wavelength. The profile acts as a notch filter, allowing only a single wavelength out of the continuous spectrum to develop predictably, following Euler-Lagrange dynamics. We argue that this understanding not only enables designing the outcomes of the breakup necessary for turning it into a technology for materializing fiber-embedded functional systems but also positions a multimaterial fiber as a universal physical simulator of capillary instability in viscous threads.

Modelling and control of hydrogen production processes based on electrolysis

Currently, hydrogen is considered as one of the most promising energy carriers, the production of which is possible from various raw materials, including water, natural gas, hydrogen sulphide, coal, etc. The article presents the main results of an analysis of global technological trends in the development of hydrogen generation methods in the period from 2010 to 2038, which aims to identify in-demand and popular technological solutions for hydrogen energy. The analysis is based on the International Energy Agency's database published in October 2022, which contains the most comprehensive information on the key characteristics of 990 hydrogen projects based in sixty countries: output, installed electrical power, carbon dioxide emissions, type of output, stage and timing of implementation. The analysis shows the steady leadership of electrolysis hydrogen generation technologies in the context of the search for the most widespread method of hydrogen production. At the same time, the global hydrogen energy industry has clearly expressed trends towards the increased introduction of alternative (non-electrolysis) technologies in large-scale industrial production. Based on the existing empirical Ullerberg model, a modified universal structural simulation model of hydrogen electrolysis generation in plants with alkaline electrolysers and with proton exchange membrane has been proposed. The modified model has been developed in MATLAB application package and Simulink dynamic simulation environment using Simscape physical simulation elements. Verification procedure of the developed model showed good agreement of simulation results with the experimental data available in the open sources and obtained at the alkaline electrolysis and proton exchange membrane electrolysis plants. To increase the energy efficiency of hydrogen production process, a single-loop system for automatic regulation of feed water temperature supplied to the proton-exchange membrane electrolysis unit was developed.

Design and implementation of a real-time simulation platform for embedded applications on general-purpose operating systems

In recent years, the number of invested resources adopted in experiments of embedded applications dropped significantly as many simulation technologies are widely used. However, the efficiency of simulations is seriously influenced by some expensive and difficult-to-obtain devices. It is urgent and of great significance to build a universal simulation platform for embedded applications on general-purpose operating systems with an objective of improving the efficiency and effectiveness of system development and implementation. Since virtualization technology can greatly enhance the simulation efficiency by providing virtual models to simulate the behaviors of real devices, this paper designs and realizes a real-time simulation platform on general-purpose operating systems with the virtualization technology such that embedded applications would be correctly and efficiently debugged and tested on the general-purpose operating systems. The proposed simulation platform contains four layers named hardware resource, virtualization, virtual runtime environment, and interface adaptation, allowing dynamic debugging and testing of embedded applications without requiring the actual presence of real devices. Experiments are conducted to verify the functionalities of the proposed simulation platform, and results demonstrate that the proposed simulation platform can meet the real-time and high reliability requirements of embedded applications.

Beyond the state of the art of reverse vaccinology: predicting vaccine efficacy with the universal immune system simulator for influenza

When it was first introduced in 2000, reverse vaccinology was defined as an in silico approach that begins with the pathogen's genomic sequence. It concludes with a list of potential proteins with a possible, but not necessarily, list of peptide candidates that need to be experimentally confirmed for vaccine production. During the subsequent years, reverse vaccinology has dramatically changed: now it consists of a large number of bioinformatics tools and processes, namely subtractive proteomics, computational vaccinology, immunoinformatics, and in silico related procedures. However, the state of the art of reverse vaccinology still misses the ability to predict the efficacy of the proposed vaccine formulation. Here, we describe how to fill the gap by introducing an advanced immune system simulator that tests the efficacy of a vaccine formulation against the disease for which it has been designed. As a working example, we entirely apply this advanced reverse vaccinology approach to design and predict the efficacy of a potential vaccine formulation against influenza H5N1. Climate change and melting glaciers are critical due to reactivating frozen viruses and emerging new pandemics. H5N1 is one of the potential strains present in icy lakes that can raise a pandemic. Investigating structural antigen protein is the most profitable therapeutic pipeline to generate an effective vaccine against H5N1. In particular, we designed a multi-epitope vaccine based on predicted epitopes of hemagglutinin and neuraminidase proteins that potentially trigger B-cells, CD4, and CD8 T-cell immune responses. Antigenicity and toxicity of all predicted CTL, Helper T-lymphocytes, and B-cells epitopes were evaluated, and both antigenic and non-allergenic epitopes were selected. From the perspective of advanced reverse vaccinology, the Universal Immune System Simulator, an in silico trial computational framework, was applied to estimate vaccine efficacy using a cohort of 100 digital patients.

An efficient modeling approach for wavelet transform processors using surface acoustic wave devices

Wavelet transform processors (WTPs) using surface acoustic wave devices provide an effective solution to utilize wavelet transform technology in practical applications. This work proposes a novel model of WTPs for predicting their performance characteristics, which might be utilized for single-electrode type and double-electrode type interdigital transducers (IDTs), as there is currently no universal, quick, and accurate simulation technology for WTPs (IDTs). The admittance matrix, transfer function, and insertion loss for both IDTs and WTPs in conjunction with a two-port electrical network are all evaluated by the model. Furthermore, some WTPs samples with a piezoelectric substrate of ST-X quartz and IDTs of Al thin film were fabricated to validate the accuracy of the simulation, with a center frequency and a scale of 60 MHz and 0.215, respectively. A comparison of the simulated and measured results found that the relative error of the frequency is only 0.67%, the maximum relative error of the bandwidth is 5.79% and the relative error of the insertion loss is only 1.24%. The experimental results show that the model is extremely accurate in effective frequency band, and its application will accelerate the design and production of WTPs, promoting the use of WTPs in signal processing systems.

Development of Universal Test Platform of Missile Launch and Control System

This paper proposes a novel hardware and software platform for missile launch and control system based on custom Ethernet bus + modular unit + synchronous clock. It consists of power unit, main control unit, MIL1553B/ARINC429 interface simulation unit, CAN/Flexray interface simulation unit, universal serial interface simulation unit, I/O interface simulation unit, video unit, stabilized voltage supply unit, chassis and other parts. Each unit adopts the modular daisy chain communication, and, through modularization of each unit, realizes the testing of maintenance objects and the expansion of new equipment testing resources in the future. Real-life application shows that the proposed hardware and software platform is reliable and effective.

3D geostatistical modelling of a tailings storage facility: Resource potential and environmental implications

The management of mine tailings presents a global challenge. Re-mining of tailings to recover remaining metals and other valuable constituents could play a crucial role in reducing the volume of stored tailings. To assess the resource potential of tailings storage facilities, 3D resource models must be constructed. This is not straightforward owing to the heterogeneous nature of tailings. In this case study, modelling of the Davidschacht tailings deposit was performed using universal sequential Gaussian simulation, to account for the strong trends and heterogeneity in chemical distribution. The tonnages of the valuable elements were estimated with reasonable certainty, confirming that relatively few drill holes are required for robust resource estimates of tailings storage facilities. Zinc is the most abundant valuable metal (∼5,170±517 t), followed by Pb (∼2,060±206 t), Cu (∼550±66 t) and In (∼11±1 t), while the toxic elements As and Cd are present in tonnages of ∼8,350±585 t and ∼47±4 t, respectively, with errors given for 95 % confidence levels. Despite the In tonnage being low compared to the other elements, its in situ value is around half that of Cu and Pb, demonstrating the importance of high value by-products for re-mining potential. Although tailings deposits typically have lower grades than primary ore deposits, and the quantities of recoverable valuable elements may be even lower due to current technological limitations, re-mining of TSFs may help to diversify raw materials supply chains and should also be considered for rehabilitation purposes. Geostatistical modelling, particularly universal kriging-based simulation, has been proven to produce robust tonnage estimates of tailings storage facilities and should be adopted in industry to reduce the technical and financial uncertainties associated with re-mining.

A quantum simulator based on locally controlled logical systems

In a digital quantum simulator, basic two-qubit interactions are manipulated by means of fast local control operations to establish a desired target Hamiltonian. Here we consider a quantum simulator based on logical systems, i.e. where several physical qubits are used to represent a single logical two-level system to obtain enhanced and simple control over effective interactions between logical systems. Fixed, distance-dependent pairwise interactions between the physical qubits lead to effective interactions between the logical systems, which can be fully controlled solely by the choice of their internal state. This allows one to directly manipulate the topology and strength of effective interactions between logical systems. We show how to choose and generate the required states of logical systems for any desired interaction pattern and topology, how to perform arbitrary logical measurements, and how to obtain full control over single logical systems using only the intrinsic two-body interactions and control of individual physical qubits. This leads to a universal quantum simulator based on logical systems. We discuss the advantages of such a logical quantum simulator over standard ones, including the possibility to reach target topologies that are only accessible with large overheads otherwise. We provide several examples of how to obtain different target interaction patterns and topologies from initial long-ranged or short-ranged qubit-qubit interactions with a specific distance dependence.

Effect of Geological Uncertainty on the Shaft Resistance Prediction and Reliability of Piles Driven in Multi-Layered Geomaterials

This study proposes a method to quantify the effect of geological uncertainty on the predicted shaft resistance and the reliability of piles driven into multi-layered geomaterials. Several geological predicted surfaces with different levels of geological uncertainties are simulated through multiple sets of boreholes using the multinomial categorical prediction approach for the spatial Markov chain. As the number of strategically placed boreholes increases, the geological uncertainties decrease. Respective ground predicted surfaces are also simulated from these geological predicted surfaces using universal kriging and conditional simulation. The shaft resistances of the piles driven at the site are estimated for the multiple geomaterials layers using geotechnical prediction equations specified for the geomaterial type. The design reliability for the shaft resistance obtained from the various geological, ground, and geotechnical predictions is thereafter accessed through its probability of failure evaluated using the Monte Carlo simulation. This methodology is applied to the Lemhi River bridge project site in Idaho. The results illustrate the influence of geological uncertainty on the design of piles driven into multi-layered geomaterials and further help in determining an optimal site investigation plan that will improve pile design.

Between SC and LOGDCFL: families of languages accepted by logarithmic-space deterministic auxiliary depth-k storage automata

The closure of deterministic context-free languages under logarithmic-space many-one reductions (-m-reductions), known as LOGDCFL, has been studied in depth from an aspect of parallel computability because it is nicely situated between and . By replacing a memory device of pushdown automata with an access-controlled storage tape, we introduce a computational model of one-way deterministic depth-k storage automata (k-sda's) whose tape cells are freely modified during the first k accesses and then become blank forever. These k-sda's naturally induce the language family . Similarly to , we study the closure of all languages in under -m-reductions. We demonstrate that by significantly extending Cook's early result (1979) of . The entire hierarch of for all therefore lies between and . As an immediate consequence, we obtain the same simulation bounds for Hibbard's limited automata. We further characterize in terms of a new machine model, called logarithmic-space deterministic auxiliary depth-k storage automata that run in polynomial time. These machines are as powerful as a polynomial-time two-way multi-head deterministic depth-k storage automata. We also provide a ‘generic’ -complete language under -m-reductions by constructing a two-way universal simulator working for all k-sda's.