Dynamic Analysis Tools Research Articles

Effect of electromagnetic radiations on the dynamics of a five-chain coupled inertial Hopfield neural network and control of multi-stability with the selection of a desired attractor.

Abstract In this paper, we investigate the effect of electromagnetic radiation on the dynamics of a network consisting of five chain-coupled inertial Hopfield neurons. The study revealed that the neural system designed such a way involves several complex phenomena, namely Hopf bifurcation, chaos, hyperchaos and the coexistence of up to thirty-two attractors in phase space. The complexity specific to our system is due to the higher number of equilibrium points, namely two hundred and forty-three. Under the conditions of safe functioning of our neural system (chaos or hyperchaos), we have been able to observe that electromagnetic radiation has a harmful character for the system, because we found for a range of variation in the intensity of the electromagnetic feedback induction current a coexistence of chaotic and periodic states (epileptic state). We then controlled the multi-stability using a desired attractor selection scheme, with the aim of suppressing the pathological state. All the work carried out in this contribution is done with the help of dynamical system analysis tools such as the bifurcation diagram, the spectrum and the maximum exponent of Lyapunov, phase portraits and basins of attraction. The scheme used is the Runge-Kutta-4. In order to validate the numerical results, we use analog calculation and some results were derived from the Pspice software. These results are in good accordance in amplitude and location on the plane to those of numerical simulations.

Managing Adverse Events in Clinical Trials with R and Shiny

Adverse events (AEs) are critical occurrences that can significantly impact patient safety and the overall success of clinical trials. Effective management of AEs is essential for ensuring regulatory compliance and safeguarding participants' well-being. This paper explores the integration of R and Shiny as innovative tools for the real-time monitoring, visualization, and analysis of AEs in clinical trials. By leveraging R’s robust statistical capabilities and Shiny’s interactive interface, researchers can enhance data management processes, facilitate informed decision- making, and foster collaboration among stakeholders. A case study is presented to illustrate the practical application of R Shiny in tracking AEs, demonstrating its effectiveness in improving trial outcomes and ensuring patient safety. The findings emphasize the need for adopting dynamic data analysis tools to optimize adverse event management in the evolving landscape of clinical research. KEYWORDS Adverse Events, Clinical Trials, R, Shiny, Data Management, Visualization, Real-Time Monitoring, Patient Safety.

Refined time-shift multiscale slope entropy: a new nonlinear dynamic analysis tool for rotating machinery fault feature extraction

Refined time-shift multiscale slope entropy: a new nonlinear dynamic analysis tool for rotating machinery fault feature extraction

TME-analyzer: a new interactive and dynamic image analysis tool that identified immune cell distances as predictors for survival of triple negative breast cancer patients

Spatial distribution of intra-tumoral immune cell populations is considered a critical determinant of tumor evolution and response to therapy. The accurate and systemic search for contexture-based predictors would be accelerated by methods that allow interactive visualization and interrogation of tumor micro-environments (TME), independent of image acquisition platforms. To this end, we have developed the TME-Analyzer, a new image analysis tool, which we have benchmarked against 2 software tools regarding densities and networks of immune effector cells using multiplexed immune-fluorescent images of triple negative breast cancer (TNBC). With the TME-Analyzer we have identified a 10-parameter classifier, predominantly featuring cellular distances, that significantly predicted overall survival, and which was validated using multiplexed ion beam time of flight images from an independent cohort. In conclusion, the TME-Analyzer enabled accurate interactive analysis of the spatial immune phenotype from different imaging platforms as well as enhanced utility and aided the discovery of contextual predictors towards the survival of TNBC patients.

Estimation of wind dynamic load linear transfer matrix using proper orthogonal decomposition method and genetic algorithm

ABSTRACT Due to the advantages of Laplace domain in both time and frequency domains, the dynamic analysis and control tools in engineering software like MATLAB and Python have been designed based on it. Dynamic analysis of structures requires determination of the overall transfer matrix, which is obtained by multiplying the structure's transfer matrix (TM) with the load TM. With the input vector of unit intensity white-noise processes and the overall TM, the structural responses can be obtained. Furthermore, having the load TM is crucial for implementation of active control systems. In this article, the TM of along-wind loads was estimated for a tall building using the proper orthogonal decomposition (POD) method and the genetic algorithm (GA). To evaluate the effectiveness of the proposed approach, an example of a tall building was provided. The wind load cross-power spectral matrix (XPSD) was decomposed using POD technique, followed by the truncation of higher loading modes. Subsequently, the loading TM was derived by estimating the target non-linear functions with linear transfer functions through GA technique. Then, the responses of the structure were computed using the loading TM. The results demonstrated the efficacy of the proposed method in acquiring the loading TM and predicting wind-induced responses.

Preliminary tritium transport analysis for the water cooled ceramic breeder blanket system based on a system level code

This paper presents a dynamic analysis tool for evaluating the tritium inventory, tritium extraction and tritium losses for the Water Cooled Ceramic Breeder (WCCB) blanket system of Chinese Fusion Engineering Test Reactor (CFETR). We have developed a program for the tritium transport analysis at the system level, which aims to estimate the tritium related quantities for the WCCB blanket system. The tritium inventory in the material defects is likewise taken into account. The sensitivity analysis is conducted on key parameters is carried out. The key output quantities of the WCCB blanket system include the tritium inventory in structural material, purge gas and coolant loops, tritium extracted by the TES and CPS, and tritium losses.

Introduction on tritium transport analysis model for HCCP breeding blanket system

In the context of implementing the He-cooled breeding blanket system for a fusion reactor, several crucial aspects need consideration. Among these, the development of a tritium transport model plays a pivotal role in ensuring safety and effective design. Given that tritium release into the environment from the breeding blanket system poses a radioactive risk, accurate calculation and prediction area essential to prevent potential incidents in a fusion reactor. To address this challenge, a collaborative effort between the Korea Institute of Fusion Energy (KFE) and the University of California, Los Angeles (UCLA) resulted in the creation of THETA-FR (Tritium/Hydrogen Enhanced dynamic Transport Analysis Tool for Fusion Reactor). THETA-FR is an integrated analysis tool that combines Matlab Simulink and COMSOL Multiphysics. Its purpose is to model and predict the dynamic transport phenomena of H isotopes (H/D/T) within the breeding blanket system. Specifically, THETA-FR focuses on transient tritium retention, permeation, and release amounts from the breeding blanket system into the environment. In this paper, we introduce the integrated system and components of THETA-FR, shedding light on various tritium behaviors within the HCCP breeding blanket FW/BU component. By leveraging THETA-FR, researchers and engineers can make informed decisions regarding tritium control and safety in fusion reactors.

Refined composite multiscale slope entropy and its application in rolling bearing fault diagnosis

Rolling bearing is the key component of rotating machinery, and its vibration signal usually exhibits nonlinear and nonstationary characteristics when failure occurs. Multiscale permutation entropy (MPE) is an effective nonlinear dynamics analysis tool, which has been successfully applied to rolling bearing fault diagnosis in recent years. However, MPE ignores the deep amplitude information when measuring the complexity of the time series and the original multiscale coarse-graining is insufficient, which requires further research and improvement. In order to protect the integrity of information structure, a novel nonlinear dynamic analysis method termed refined composite multiscale slope entropy (RCMSlE) is proposed in this paper, which introduced the concept of refined composite to further boost the performance of MPE in nonlinear dynamical complexity analysis. Furthermore, RCMSlE utilizes a novel symbolic representation that takes full account of mode and amplitude information, which overcomes the weaknesses in describing the complexity and regularity of bearing signals. Based on this, a GWO-SVM multi-classifier is introduced to fulfill mode recognition, and then a new intelligent fault diagnosis method for rolling bearing based on RCMSlE and GWO-SVM is proposed. The experimental results show that the proposed method can not only accurately identify different fault types and degrees of rolling bearing, but also has a short computation time and better performance than other comparative methods.

Dynamic Load Analysis of Mine-Truck Using Multibody Dynamic Analysis Method

Abstract: Vehicle load distributed on front & rear axle assembly during various working conditions is one of the most important factors influencing working performance and service life of drive axle assembly. The dynamic load on axle assembly is higher compared to the rated load because of variations in vehicle speed and road surface conditions. Early failure of structural components is caused because of higher dynamic reaction forces due to uneven road profiles. The dynamic load calculation of axle assembly is presented in this paper for a Mine-truck with various road conditions and vehicle speeds. The road load conditions consist of grade, bump & path hole. Mine-truck with payload capacities of 63 Ton is considered for the study. The behaviour of vertical force is calculated for different vehicle speeds (3 - 12 km/hr.) of the machine on the front & rear axle assembly during running conditions. Multi-body dynamic Analysis tool ADAMS is used for this study. ADAMS helps to study the dynamics of moving parts and load distribution throughout mechanical systems during motion. The Mine-truck3D model was created with the help of computer-aided design (CAD) software. Major units of Mine trucks are considered to prepare 3D models like Cabin-engine mass, Bucket, front axle assembly, rear Axle assembly & tires. Multi-body vehicle models are prepared in simulation software ADAMS by importing 3D models prepared by computer-aided design (CAD) software. This provides guidelines for selecting dynamic load factors while designing structural parts of the vehicle.

System Identification and Dynamic Analysis of the Propulsion Shaft Systems Using Response Surface Optimization Technique

Marine vessels rely heavily on propeller shaft systems to adjust the engine torque and propeller thrust. However, these systems are subjected to various dynamic excitations during operation, such as transverse, longitudinal, and torsional excitations. These excitations can arise from factors like non-uniform stern flow fields, misaligned components, and the whirling motion of the shafts, which can affect the integrity and reliability of the vehicle. To analyze the dynamic response of the propulsion shaft system and ensure its reliability, numerical/analytical models are currently in practice. The finite element method (FEM) is a popular choice, but uncertainties in bearings and connectors stiffness lead to inaccuracies in the Finite Element model, resulting in significant differences between the experimental and theoretical models. This paper proposes the response surface optimization (RSO) technique to estimate unknown bearing stiffness in the propulsion shaft system. The experimental model of the propeller shaft system is constructed using steady-state response with step sine excitation. The RSO technique is then used to update the natural frequencies and vibration amplitude of the FE (Finite Element) model. The updated model shows less than a 10% difference in natural frequencies and vibration amplitude compared to the experimental model, demonstrating that the proposed technique is an efficient tool for marine shaft dynamic analysis.

Analysis of information flow security using software implementing business logic based on stored database program blocks

Objectives. Verification of software security is typically performed using dynamic and static analysis tools. The corresponding types of analysis do not usually consider the business logic of the software and do not rely on data access control policies. A modern approach to resolving this problem is to implement language-based information flow control. Despite a large amount of research, mechanisms for information flow control in software are not widely used in practice. This is because they are complex and impose increased demands on developers. The aim of the work is to transfer information flow control from the language level to the level of formal verification. This will enable the functions of controlling data integrity and confidentiality in software to be isolated into a separate task, which can be resolved by information security analysts.Methods. The research is based on general formal security methods for computer systems and formal verification methods. The algorithm developed by the author for checking security specifications and resolving security violations uses temporal logic of actions.Results. The technology is presented as a step-by-step approach to resolving specific tasks, including the following: designing a database (DB) for storing and processing sensitive information; analyzing dependencies and identifying relevant sets of program blocks in the DB; generating TLA+ specifications for the identified program blocks; labeling specifications according to global security policy rules and additional constraints; applying the specification verification algorithm, and resolving security violations while providing recommendations for software developers. The procedure also involves analyzing labeled data, in order to control the spread of verified program block output values in external software modules.Conclusions. The technology presented herein does not require developers to include redundant annotations describing security policy rules. The function of analyzing information flows with reference to predefined access restrictions is moved to a separate stage of the software development life cycle.

Dynamic Competitiveness of Indonesian Commodities in Major Export Destination

This study aims to analyze the export competitiveness and market position of the agricultural, manufacturing, and mining sectors in 10 main export destination countries (China, the United States, Japan, India, Singapore, Malaysia, South Korea, Thailand, the Netherlands, and the Philippines). This study uses secondary data sourced from UN COMTRADE for the period of 2013 – 2018. The data is categorized using a 2-digit Harmonized System (HS) classification. This study uses Revealed Comparative Advantage (RCA) and Export Product Dynamics (EPD) analysis tools. The RCA estimation results show the export competitiveness of Indonesia’s agricultural, industrial, and mining products is still weak and strong in several major export destination countries. Meanwhile, the EPD estimation shows the Indonesia’s exports of agricultural, industry, and mining commodities mostly got rising star positions in some countries but losing opportunity positions in some other countries. The following suggestions proposed are based on the research. In general, the implications of policy to improve the competitiveness of export products in the manufacturing, agriculture, and mining industries are infrastructure improvement, expansion of the export market, improvement in the quality of human resources, and employment, increasing access to finance, increasing the quality and quantity of production in processing, agriculture and mining industries, and maintaining political

A comprehensive study on seismic dynamic responses of stochastic structures using sparse grid-based polynomial chaos expansion

The seismic response is a critical aspect of structural engineering, as it directly influences the design and safety evaluation of such systems. Structural seismic response becomes more complicated when unavoidable uncertainties in the structure are considered. Therefore, solving and analyzing the stochastic dynamic response of structures efficiently and accurately is of great significance. Various uncertainty quantification methods such as the stochastic finite element method, Monte Carlo method, and polynomial chaos expansion method have made significant progress in this field. However, these methods do not provide a comprehensive study of the seismic response of stochastic structures and efficiency problems rapidly emerge as the number of random variables increases. This paper delivers a comprehensive study of the seismic dynamic response of space truss and reticulated shell structure considering uncertainties in material properties, geometry, and loading. To this end, the finite element model of the structure was first modeled and the deterministic solutions were obtained. Then, polynomial surrogates are modeled for the natural frequency, mode participation factor, mode superposition response, and transient response of the structure under stochastic uncertainties. The sparse grid technique is used to select sparse quadrature points, which overcomes the curse of dimensionality caused by full grid integration. The results demonstrate that the sparse grid-based polynomial chaos expansion is more efficient. Uncertainty quantification reveals the uncertainty of modal analysis, response spectrum analysis, and transient response analysis of space truss and reticulated shell under seismic excitation. In summary, this study provides valuable insights and an efficient and accurate uncertainty quantification tool for the seismic dynamic analysis of stochastic structures, ultimately contributing to safer and more robust structural designs.

Methodology for Reverse Engineering of Machine Code. Part 3. Dynamic Investigation and Documentation

The results of creating a unified methodology for reverse engineering the machine code of devices are presented. This, the third and final part of the series of articles, is devoted to the dynamic examination of code in order to restore metainformation about it and additionally search for vulnerabilities, as well as the final documentation of the results. A review of scientific publications on the topic of existing methods and tools for dynamic analysis of machine code is carried out. A detailed description and formalization of the steps of the stage is given, as well as examples of their application in practice. A complete diagram of the proposed methodology is presented in graphical form, indicating the main and intermediate results obtained. All steps are summarized in a summary table, which also contains some of their characteristics. The shortcomings of the methodology and ways to eliminate them are discussed.

Dynamical analysis of a new 3D chaotic system: non-equilibrium point, conservative, rotationally hidden attractor

A novel three-dimensional chaotic system is proposed in this paper. The nonlinear features are enhanced by adding e-exponent function to make the system behavior more complex and diverse. Through calculation and experimental verification, it is found that the system is a conservative system without equilibrium point, and this kind of system may produce hidden dynamic behavior. Therefore, four different dynamic analysis tools are chosen to simulate the possible hidden dynamics. The rotation factor is used to create some new models on the original system equation. With constantly adjustments of the rotation angle, the different resulting rotational hidden attractors are used to further prove that such chaos exists in the new proposed system. In the end, the realization of DSP shows the feasibility of this system in practical applications.

Data Center Energy Evaluation Tool Development and Analysis of Power Usage Effectiveness with Different Economizer Types in Various Climate Zones

Data centers are energy-intensive facilities, with over 95% of their total cooling load attributed to the heat generated by information technology equipment (ITE). Various energy-saving techniques have been employed to enhance data center efficiency and to reduce power usage effectiveness (PUE). Among these, economizers using outdoor air for cooling are the most effective for addressing year-round cooling demands. Despite the simplicity of the load composition, analyzing data center cooling systems involves dynamic considerations, such as weather conditions, system conditions, and economizer control. A PUE interpretation tool was specifically developed for use in data centers, aimed at addressing the simplicity of data center loads and the complexity of system analysis. The tool was verified through a comparison with results from DesignBuilder implementing the EnergyPlus algorithm. Using the developed tool, a comparative analysis of economizer strategies based on the PUE distribution was conducted, with the aim of reducing the PUE of data centers across various climatic zones. The inclusion of evaporative cooling (EC) further improved cooling efficiency, leading to reductions in PUE by approximately 0.02 to 0.05 in dry zones. Additionally, wet zones exhibited PUE reductions, ranging from approximately 0.03 to 0.07, with the implementation of indirect air-side economizer (IASE). Sensitivity and uncertainty analysis were further conducted. The computer room air handler (CRAH) supply temperature and CRAH temperature difference were the most influential factors affecting the annual PUE. For the direct air-side economizer (DASE) and DASE + EC systems, higher PUE uncertainty was observed in zones 1B, 3B, 4B, and 5B, showing ranges of 1.17–1.39 and 1.15–1.17, respectively. In the case of the IASE and IASE + EC systems, higher PUE uncertainty was noted in zones 0A, 0B, 1A, 1B, and 2A, with ranges of 1.22–1.43 and 1.17–1.43, respectively. The distinctive innovation of the tool developed in this study is characterized by its integration of specific features unique to data centers. It streamlines the computation of cooling loads, thus minimizing the burden of input, and delivers energy consumption data for data center cooling systems with a level of precision comparable to that of commercial dynamic energy analysis tools. It provides data center engineers with a valuable resource to identify optimal alternatives and system design conditions for data centers. This empowers them to make informed decisions based on energy efficiency enhancements, thereby strengthening their ability to improve energy efficiency.

Impact Testing of Different Materials on Wheels Used in Throwable Unmanned Ground Vehicles

Throwable Unmanned Ground Vehicles are light weight, small size, easily deployable and impact resistive vehicles mainly used in domestic as well as in military purposes where human life is compromised such as inspection of sewage pipes, and search and rescue operations etc. Main challenge while considering a Throwable UGV is its impact absorption capability which is seen through its material properties. Wheels of Throwable UGV absorb most of the impact without harming the internal structure. To solve this problem a honeycomb structured wheel is designed and simulated in ANSYS Workbench. Vulcanized rubber and Plastic composite PCTPE material wheels were impact tested using explicit dynamic analysis tool in ANSYS workbench. Total deformation, equivalent stress and strain results are tested in ANSYS under impact testing of wheel which is dropped from 10 meter height with velocity of 14m/s in a concrete surface. A plastic composite material PCTPE was 3D-printed and was used in Throwable Unmanned Ground Vehicle.

MicroProf : Code-level Attribution of Unnecessary Data Transfer in Microservice Applications

The microservice architecture style has gained popularity due to its ability to fault isolation, ease of scaling applications, and developer’s agility. However, writing applications in the microservice design style has its challenges. Due to the loosely coupled nature, services communicate with others through standard communication APIs. This incurs significant overhead in the application due to communication protocol and data transformation. An inefficient service communication at the microservice application logic can further overwhelm the application. We perform a grey literature review showing that unnecessary data transfer is a real challenge in the industry. To the best of our knowledge, no effective tool is currently available to accurately identify the origins of unnecessary microservice communications that lead to significant performance overhead and provide guidance for optimization. To bridge the knowledge gap, we propose MicroProf , a dynamic program analysis tool to detect unnecessary data transfer in Java-based microservice applications. At the implementation level, MicroProf proposes novel techniques such as remote object sampling and hardware debug registers to monitor remote object usage. MicroProf reports the unnecessary data transfer at the application source code level. Furthermore, MicroProf pinpoints the opportunities for communication API optimization. MicroProf is evaluated on four well-known applications involving two real-world applications and two benchmarks, identifying five inefficient remote invocations. Guided by MicroProf , API optimization achieves an 87.5% reduction in the number of fields within REST API responses. The empirical evaluation further reveals that the optimized services experience a speedup of up to 4.59×.

Concept of Computational Fluid Dynamics Design and Analysis Tool for Food Industry: A Bibliometric

Technology that is currently in demand is CFD. By simulating fluid flow around a product on a computer, the computational fluid dynamics (CFD) technique allows designers of new products to be tested. This research aims to analyze the bibliometrics of CFD publications as a design tool in the food industry to determine concepts, trends, and contributions of previous research. Computational Fluid Dynamics (CFD) is a technology used to test product designs through computer simulations of fluid flow around the product. The use of technology in various industries, such as the food industry, is essential to create better products or services. This research uses a bibliometric analysis method supported by theoretical analysis. This research consists of 5 steps, namely (i) determining the research theme for formulating keywords, (ii) collecting publication documents, (iii) data processing, (iv) bibliometric analysis, and (v) preparing a report. The keywords used in this research are "Computational Fluid Dynamics Design (CFD) in Food Industry." The results of the publication search found a total of 211 documents from 1992 to 2023. The average number of publications was 6.59. The trend of CFD publications in the food industry was first carried out in 1992. The development of this publication has been fluctuating, and there has been an increase in publications in the last five years (2019 - 2023). Research publications regarding CFD in the food industry are grouped into 20 subject areas. Contributions to this research consisted of 159 authors, 160 affiliates, and 51 countries. Completing this research will likely provide information regarding publication sources and contributions made by several scientists from various affiliates and countries worldwide.

Energy performance assessment of a solar-driven thermochemical cycle device for green hydrogen production

This paper presents a novel dynamic simulation model for assessing the energy performance of solar-driven systems employed in green hydrogen production. The system consists of a parabolic dish collector that focuses solar radiation on two cerium-based thermochemical reactors. The model is based on a transient finite-difference method to simulate the thermal behaviour of the system and it integrates a theoretical analysis of materials and operating principles. Different empirical data were considered for experimentally validating it: a good agreement between experimental and simulated results was obtained for the temperatures calculated inside the thermochemical reactor (R2 = 0.99, MAPE = 6.3%) and the hourly flow rates of hydrogen, oxygen, and carbon monoxide (R2 = 0.96, MAPE = 10%) inside the thermochemical reactor. The model was implemented in a MatLab tool for the system dynamic analysis under different boundary conditions. Subsequently, to explore the capability of this approach, the developed tool was used for analysing the examined device operating in twelve different weather zones. The obtained results comprise heat maps of specific crucial instants and hourly dynamic trends showing redox reaction cycles occurring into the thermochemical reactors. The yearly hydrogen production ranges from 1.19 m3/y to 1.64 m3/y according to the hourly incident solar radiations, outdoor air temperatures and wind speeds. New graphic tools for rapid feasibility studies are presented. The developed tools and the obtained results can be useful to the basic design of this technology and for the multi-objective optimization of its layout and main design/operating parameters.