Analysis Of Engineering Systems Research Articles

Efficient basis-adaptive Bayesian compressive sensing with fast leave-one-out cross-validation for reliability analysis of geotechnical engineering systems

For complex geotechnical engineering systems with highly non-stationary responses and computationally time-consuming deterministic models, the estimation of failure probability poses a significant challenge in engineering. The non-parametric Bayesian compressive sensing (BCS)-based response surface method (RSM) has demonstrated its effectiveness as a surrogate modeling method for the reliability analysis of highly non-stationary systems. However, the performance of the BCS-based RSM heavily depends on the selection of basis functions. Incorporation of inappropriate basis functions can lead to under-fitting or over-fitting, particularly in cases of sparse sampling data. Therefore, selecting the optimal basis function is crucial to ensure the accuracy of the BCS-based response surface for reliability analysis of geotechnical systems. This study develops a novel BCS-based RSM, utilizing the analytical fast Leave-one-out cross-validation (LOOCV) method for the adaptive selection of basis functions, denoted as the BCS-LOOCV method, to effectively address this challenge in the reliability analysis of highly non-stationary geotechnical systems. In the proposed BCS-LOOCV method, the LOOCV error serves as the model selection criterion, and the optimal basis functions with the minimum LOOCV error are adaptively identified based on sparse sampling data through an efficient model comparison and selection process. Investigations using a highly non-stationary function and two slope reliability analysis problems demonstrate the reliable performance of the proposed BCS-LOOCV method.

Refined finite element analysis of helical wire ropes under multi-axial dynamic loading

Due to high tensile strength, light weight, and good flexibility, the steel wire ropes with helical structures are widely used as crucial load-bearing components in various industrial sectors such as civil engineering. They are subjected to significant vibrations caused by multi-axial dynamic loading during the service period which may eventually result in premature failures. This paper presents a refined finite element analysis method for helical wire ropes under multi-axial dynamic loading. The proposed method employs multi-directional dynamic excitations extracted from the analysis of the overall engineering systems to consider actual loading conditions. Refined finite element analysis of the entire steel wire rope under multi-axial dynamic loading is carried out for the first time based on the global-local finite element model to obtain detailed mechanical responses. The critical rope segment is represented by solid elements taking into account the helical structure, inter-wire frictional contact, slippage, and material nonlinearity, among others, and non-critical segments are simulated with beam elements in the established global-local model, which can achieve good balance between computational efficiency and accuracy. The refined finite element modeling strategy is validated via three numerical examples with comparisons against the results in the literature. The proposed method is illustrated on the suspender cable used in suspension bridges. Detailed mechanical responses and their influencing factors are examined to acquire new insights into the dynamic mechanical characteristics of typical double-helical wire rope. The present work can provide an efficient tool for the assessment of in-service engineering systems containing helical wire ropes.

Bifurcation and multi-stability analysis of microwave engineering systems: Insights from the Burger–Fisher equation

The present article depicts the research being done on the microwave effect realized by the often-used Burger–Fisher equation. A particular view is on the emergence of multi-stability and the bifurcations associated with microwave engineering systems. A novel rational, trigonometric, and hyperbolic form of the traveling waves is furnished by the resolution of the non-linear issue with the aid of the advanced exp (−Ψ(η))-expansion function parameterization. Firstly, we will solve the exact form of the Burger–Fisher equation, which clarifies the behavior of the equation in different conditions. Subsequently, bifurcation analysis techniques will be employed to study the nuanced relationship between the system parameters and the emergence of multistability phenomena. Through our results, we exposed the complicated essential features of microwave physics and established crucial parameters that determine a system’s behavior. Next, we cover control principle issues and practical applications in microwave engineering problems. This model accommodates the essential features of multi-stable dynamic systems and provides an important framework for creating microwave devices and circuits.The main aim of this research work is to analyze the phenomenon of multi-stability and bifurcation in microwave engineering systems by applying Burger–Fisher equation. The study intends to obtain new solutions to the PDEs through the application of a new method, the exp (−Ψ(η))-expansion function method that uses rational, trigonometric, and hyperbolic traveling wave solutions. Existing research of the Burger–Fisher equation is not explicit and by solving the exact form the research aims at exploring the different conditions under which the equation behaves and studying the delicate interactions between the parameters of the multistable system.

An efficient surrogate model for system reliability with multiple failure modes

AbstractThe failure modes of complex systems are often highly dependent. Aiming at the reliability analysis of engineering systems with multiple failure modes, an efficient surrogate model for system reliability with multiple failure modes is proposed, namely, the Copula Adaptive Kriging surrogate model (CAKSM). First, the initial Kriging model is established based on the initial samples. In order to select more effective added samples to update the Kriging model, a new learning function, namely, Copula Unites with Expected Improvement Function (CUEIF), is established. The function can make a reasonable sample selection by considering the failure correlation. Then, based on the optimal Copula function, the reliability data of each failure mode are coupled and analyzed. In order to adapt to various computing scales, regularization is introduced to improve the prediction speed of the surrogate model, and the probability density function of each performance function is obtained by introducing nonparametric kernel density estimation. Finally, the effectiveness of the CAKSM method and the learning function CUEIF is verified through four examples.

From Sensors to Standardized Financial Reports: A Proposed Automated Accounting System Integrating IoT, Blockchain, and XBRL

Modern advances in technology have increased the demand for traditional accounting systems to be upgraded for real-time data processing, security, and standardized reports. Thus, this paper proposes a new accounting information system that integrates IoT, blockchain, and XBRL. The proposed system aims to automate the accounting process by using IoT to collect data and send it automatically to a blockchain, which acts as a database that will generate journal entries automatically through smart contracts. XBRL will then be used as an output method for standardized financial reports based on the data transferred from the blockchain. This paper uses a qualitative research design based on semi-structured interviews with 13 industry experts from IT engineering, academia, and financial systems analysis. NVivo software was used to conduct a thematic analysis of interview transcripts. The findings demonstrated that integrating IoT, blockchain, and XBRL is technically feasible, with significant potential to enhance accounting systems. Additionally, the findings identified key challenges of the proposed system, including the complexity of integration, data validation across technologies, costs, user adoption, and scalability concerns. However, the results showed that this system offers substantial benefits, such as real-time data capture from IoT devices, secure data storage and immutability through blockchain, standardized financial reporting via XBRL, accounting process automation, improved data accuracy, and enhanced security and transparency in financial reporting. The study also identified an optimal mechanism for ensuring seamless data transmission between these technologies. The study makes a valuable contribution to the accounting field by providing a new framework for automating data collection, enhancing data security, and streamlining financial reporting, with significant potential to advance accounting systems and improve transparency, accuracy, and efficiency in financial reporting. The study’s potential to impact accounting systems and financial reporting research and practice emphasizes its importance.

ANALYSIS OF THE CAUSES OF CYLINDER HEAD FAILURE OF INTERNAL COMBUSTION ENGINES

The problem of failure of the cylinder head of an internal combustion engine is considered. The factors influencing the reliability of the cylinder head over a given service life are analyzed. Among the areas that suffer the most are considered: partition between valves and between the valve and the nozzle, exhaust channels, attachment points, the plane of the surface that is in contact with the block. An analysis of existing works was carried out. Usually, the issue of reliability of a separate zone is solved, about which you can find many articles and patents. To date, there are no known works that comprehensively consider the problem of the reliability of all problem areas related to the cylinder head. This work describes the nature of the influence on the stressed state of the cylinder head from various factors: temperature loads, loads from the pressure of the working body in the cylinder, loads arising during fastening. Ways to solve problems with the reliability of individual elements exist and are being solved by many researchers, but the expediency of their implementation is ambiguous. Thus, improving heat removal from the hottest surfaces can lead to an increase in the share of influence from other factors. Solving the problem of reliability requires comprehensive consideration and a comprehensive approach. Thus, when modernizing or developing a new design, it becomes mandatory to carry out a calculation study taking into account the most complete range of factors affecting the system, which combines all the constituent elements included in this node. Modern engineering analysis systems allow such studies to be performed. It is also important to have sufficient knowledge about the properties of materials, which significantly affects the quality of the results of calculation studies. The change in heat dissipation parameters over time can be taken into account with the help of boundary conditions, which will allow us to study how the cylinder head will behave after some time of operation.

Bifurcation analysis of piecewise-smooth engineering systems with delays through numeric continuation of periodic orbits

This paper presents a numeric continuation framework for periodic orbits of piecewise-smooth and hybrid dynamical systems with fixed point delays. For the numeric solution of the corresponding infinite dimensional multi-point boundary value problem, a novel discretization and interpolation scheme is developed employing Chebyshev polynomial based spectral collocation techniques. The same approach is employed for the formulation of the corresponding monodromy matrix enabling stability analysis on the found periodic orbits. Special care is attributed to the accurate detection of discontinuity induced bifurcations such as grazing and sliding, and the implemented pseudo-arclength framework is adapted to allow two parameter continuation of these critical points. The capabilities of the developed algorithms are demonstrated on a set of delayed piecewise-smooth and hybrid dynamical systems, showcasing potential engineering applications from the fields of control theory, traffic dynamics modelling, and machine tool vibrations. Finally, a detailed tutorial is attached in the appendix to accompany the open-source release of the developed codebase.

Implementation of a Digital Model of Thermal Characteristics Based on the Temperature Field

Introduction. Computer modeling allows engineers to make valid design decisions by accurately assessing the thermal characteristics of design objects. The implementation of digital twin technology in the process of designing technical facilities is the current direction of scientific research and development. To do this, it is necessary to develop computer models whose accuracy meets the requirements for digital twins. However, the scientific literature does not widely present the results of research aimed at implementing digital twin technology in the design process. The general issues related to the use of digital twins in various industries are mainly considered. Therefore, the objective of this study was the development of a digital model and a comparative analysis of the accuracy of calculations of thermal characteristics of the design object.Materials and Methods. The main tool for conducting the research was the methodology proposed by the authors for developing a computer model of thermal characteristics for the implementation of digital twin technology. The numerical solution was implemented through constructing a thermal model for calculating the temperature field based on the finite element method in the ANSYS engineering analysis system from ANSYS, Inc. (USA). For the analytical solution, a computer model of thermal characteristics developed on the basis of the state-space method, implemented in the ANSYS Twin Builder module, was used. The state-space model was matched to the behavior of the original thermal model through approximating the transfer function to the stepwise response of the thermal load using the time domain vector approximation method. Verification of the constructed analytical model was carried out in the engineering calculation system MATLAB from the MathWorks company (USA). The research was carried out for a 400V machine model manufactured by NPO “Stankostroenie” LLC, Sterlitamak (Russia).Results. The developed digital model makes it possible to calculate the thermal characteristics of the design object with high accuracy. The results of the comparative analysis showed a high degree of correspondence between the values of thermal characteristics obtained using the proposed digital model and the results of numerical simulation. The maximum error in calculating thermal characteristics did not exceed 0.1ºC.Discussion and Conclusion. Computer modeling that combines numerical calculation methods and a scientific approach based on digital twin technology, provides obtaining the result as close as possible to the results of experiments. The digital model proposed in the study is an effective solution, since it provides performing calculations to evaluate thermal characteristics in real time, which is one of the most important requirements for the implementation of digital twin technology.

A reliability analysis method for fuzzy multi-state system with common cause failure based on improved the weakest T-norm

Recently, the reliability analysis of complex engineering systems has been confronted with a range of challenges, including fuzziness, multiple states, and common cause failures. In particular, factors such as changes in the working environment and human error contribute to the fuzzy probability value for each state in the system, which brings great challenges to its reliability analysis. In this paper, a new reliability analysis method for fuzzy multi-state system with common cause failure is proposed, which developed the fault tree analysis method and fuzzy set theory. First, a model integrating common cause failure with fuzzy T-S fault tree analysis model has been illustrated, and the equivalent model is given. Meanwhile, a novel fuzzy arithmetic method based on the weakest n-dimension T-norm is designed to solve the proposed model. Finally, the aircraft power system is analyzed as an example to verify the effectiveness of the proposed method. The result shows that the proposed method effectively enhances the capacity of failure tree analysis in assessing the reliability of complex systems characterized by multiple states, fuzziness, and common cause failures.

Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) for Early Design of Helicopter Primary Parameters

The design of a helicopter involves multiple disciplines and a large number of technical parameters with conflicting objectives, leading to the challenges of multidisciplinary coupling in design and optimization. In the context of the application of Model-Based Systems Engineering (MBSE) in complex product design, how to bridge the gap between MBSE and Multidisciplinary Design Analysis and Optimization (MDAO) to accelerate the early design process of helicopters remains an urgent problem to be addressed. The paper proposed an optimization framework that links MBSE and MDAO models for the design optimization problem of helicopters. On the MBSE side, the design optimization problem of helicopters was defined through the descriptive SysML model. On the MDAO side, the specific domain analysis model and optimization analysis workflow were established. The integration of design data was achieved through stereotype plugins and design components, bridging the gap between MBSE and MDAO, and providing accurate engineering data for system design verification. The paper provided an optimization case of a helicopter, with the optimal mission performance of the helicopter as the objective function. Through MDAO analysis, the design optimization of fuel consumption, take-off weight, and rotor dynamics parameters was completed, achieving an integrated process of system design and optimization.

A domain decomposition solver for spectral stochastic finite element: an approximate sparse expansion approach

Spectral stochastic finite element (SSFE) has been widely used in the uncertainty quantification of real-life problems. However, the prohibitive computational burden prevents the application of the method in practical engineering systems because an enormous augmented system has to be solved. Although the domain decomposition method has been introduced to SSFE to improve the efficiency for the solution of the augmented system, there still exist significant challenges in solving the extended Schur complement (e-SC) system from domain decomposition method. In this paper, we develop an approximate sparse expansion-based domain decomposition solver to generalize the application of SSFE. An approximate sparse expansion is first presented for the subdomain-level augmented matrix so that the computational cost in each iteration of the preconditioned conjugate gradient is greatly alleviated. Based on the developed sparse expansion, we further establish an approximate sparse preconditioner to accelerate the convergence of the preconditioned conjugate gradient. The developed approximate sparse expansion-based domain decomposition solver is then incorporated in the context of SSFE. Since the difficulties of solving the e-SC system have been overcome, the developed approximate sparse expansion-based solver greatly improves the computational efficiency of the solution of the e-SC system, and thereby, the SSFE is capable of dealing with large-scale engineering systems. Two numerical examples demonstrate that the developed method can significantly enhance the efficiency for the stochastic response analysis of practical engineering systems.

Feasibility study of a Solar Electric Propulsion mission to Mars

Traditionally, space missions to outer planets have relied on large amounts of chemical propellant or flybys to achieve their objectives. This large mass consumption may be significantly reduced using electric propulsion (EP), since it allows for larger specific impulses. However, this improvement is counteracted by the lower thrust per power levels achievable with EP engines compared to chemical thrusters. Here we discuss how to find a balance for a purely solar EP (SEP) uncrewed mission to Mars. We present system engineering and mission analyses focused on the orbital mechanics. The result is the conceptual design of a realistic mission to Mars, in which any target orbit around Mars can be reached using solely present SEP technology. In particular, for a 2000 kg spacecraft propelled with a Hall effect thruster (HET), the interplanetary transfer can be performed in 363 days with less than 400 kg of fuel consumption, provided that the vehicle leaves the Earth orbit with a suitable specific energy that is attainable using current launchers. Subsequently, 300 kg of propellant are sufficient to allow for the planetary capture, plane change, and circularisation manoeuvres, finally inserting the spacecraft into a polar orbit of height between 300 km and 1000 km above the surface of Mars.

Heating, Ventilation, and Air Conditioning (HVAC) Engineering Design Methods and System Analysis

Heating, Ventilation, and Air Conditioning (HVAC) Engineering Design Methods and System Analysis

Research on the Application of Operational Optimization Expert Analysis System Technology

At present, the national power system is gradually achieving separation of government and enterprise, and corporate restructuring; Implement the separation of network factories and bidding for online access, and gradually establish a modern enterprise system. Effectively carrying out energy conservation and consumption reduction work, reducing the cost of power generation and supply, is an inevitable requirement for the survival and development of power enterprises themselves.To effectively carry out energy-saving and consumption reduction work, as a group power generation company and power plant, it is necessary to solve the following problems: how to evaluate the actual and expected level of unit performance, how to quantitatively determine the impact of various factors on unit performance, how to improve operational level to reduce energy consumption, how to assess and evaluate the implementation of energy-saving work from a management perspective, and so on. Therefore, it is necessary to have a complete and scientific expert analysis system for optimizing power plant operation.

Research of PM-ADC scheme for optimized computational CFD analysis in fast reactor cores

Several challenges exist in the analysis of the sodium-cooled fast reactor (SFR) core using computational fluid dynamics (CFD)codes. These include the intricate task of geometric modeling and mesh partitioning and the substantial computational resources required by CFD calculations. These challenges have been shown to create significant impediments to the practical analysis of the SFR core. This paper proposes a CFD scheme called the Parameterized Modeling and Automated Distributed Computing Approach (PM-ADC) to address the challenges. This approach includes a fuel assembly model tailored for the fast reactor core and incorporates parameterized geometric modeling coupled with a system to automate the distribution of parallel computing. The PM-ADC scheme is divided into two critical components: rapid preprocessing design and the generation of geometric models and meshes for core assemblies, enabled by Parameterized Modeling (PM). In contrast, the Automatic Distributed Computing (ADC) component is responsible for the enhancement of computing efficiency and resource utilization. This is achieved by the automatic allocation and distribution of CFD computing resources within a partitioned domain, resulting in the completion of CFD analyses for all fuel assemblies at full height in a significantly reduced timeframe. The performance of the PM-ADC scheme is analyzed on CFD calculations on representative areas of 81 fuel assemblies within the core of the Chinese Experimental Fast Reactor (CEFR). The results show that the PM-ADC scheme can accurately and efficiently simulate the flow and heat transfer characteristics of the CEFR fuel assembly, demonstrating its potential for high-fidelity analysis of large engineering systems. The study's findings also provide new insights and tools for the ongoing development and analysis of SFRs, contributing to the evolution of nuclear reactor design and safety.

WONKA: An Ontology‐Aided Model‐Based Systems Engineering Analysis for Early V&V on Heterogeneous Systems and Applications

ABSTRACTThis research is undertaken as part of the EU‐funded EnerMan project aiming at improving the energy sustainability of manufacturing systems. In such a large project, with 22 partners over 10 countries, a first challenge addresses the collaborative design of an energy management system (EnMS) for the improvement of energy sustainability, while offering the flexibility and agility necessary for the diversity of the industrial cases studied and the partners involved. In a second stage, industrial use cases are generally too constrained to easily proceed to the verification and validation (V&V) of the scientific approaches tackling their challenges. In this context, our research contributions consist of methodologies and automated approaches to: (i) ensure the consistent collaborative integrability of developments, in a sustainable manufacturing context, and (ii) perform the verification and validation of such contributions on multiple systems, assessing their scalability on heterogeneous systems, environments, and missions in a V&V context.

Engineering systems analysis of mobility in Odawara city: New transportation services impacts on community engagement

AbstractLocal cities in Japan are struggling with aging and decreasing populations. Elderly people and parents with young children are uniquely challenged when accessing public transportation, a key to increasing their community engagement and improving local cities' sustainability. This research investigates the introduction of new transportation modes and fares on community engagement of both elderly people and parents of young children. An urban systems model which integrates mobility and civic functions is evaluated by agent‐based simulation to analyze various policies’ impacts on community engagement and financial performance. The model is applied to Odawara City, a typical local city of nearly 200,000 people in Japan. For this case study, two policies which strongly subsidize a community bus and partially subsidize a door‐to‐door van were predicted to generate 10% or greater engagement for the elderly without a financial loss compared to the current baseline case. More specifically, community engagement of elderly people and parents with young children are predicted to increase by 11% with positive (0.25 M yen) net present value per person when the fare of community buses is 100 yen and that of door‐to‐door vans is 300 yen. However, no synergistic effect driven by policies favoring elderly people and those favoring parents is found. Still, the measures to support elderly people's transportation accessibility do not harm the parents’ behavior but rather support their daily activities. The method is demonstrated to be useful for designing new mobility policy in light of a specific population with demographic residential distribution and existing transportation network.

A multi-fidelity stochastic simulation scheme for estimation of small failure probabilities

Computing small failure probabilities is often of interest in the reliability analysis of engineering systems. However, this task can be computationally demanding since many evaluations of expensive high-fidelity models are often required. To address this, a multi-fidelity approach is proposed in this work within the setting of stratified sampling. The overall idea is to reduce the required number of high-fidelity model runs by integrating the information provided by different levels of model fidelity while maintaining accuracy in estimating the failure probabilities. More specifically, strata-wise multi-fidelity models are established based on Gaussian process models to efficiently predict the high-fidelity response and the system collapse from the low-fidelity response. Due to the reduced computational cost of the low-fidelity models, the multi-fidelity approach can achieve a significant speedup in estimating small failure probabilities associated with high-fidelity models. The effectiveness and efficiency of the proposed multi-fidelity stochastic simulation scheme are validated through an application to a two-story two-bay steel building under extreme winds.

THE USAGE OF COMPUTER-AIDED ENGINEERING SYSTEM “SOLIDWORKS MOTION” TO SOLVE THE PROBLEMS OF KINEMATICS AND DYNAMICS OF TECHNICAL SYSTEMS

The paper is dedicated to the problems of engineering analysis of technical systems by means of computer modeling, in particular the calculation of kinematic and dynamic characteristics of mechanisms and machines using the Computer-Aided Engineering system – SOLIDWORKS Motion, that allows to conduct numerical experiments to check the working capacity of mechanisms and machines, determine their main kinematical and dynamical characteristics, including for the purpose of further optimization according to various criteria. The paper shows results of the performed calculations of various types of mechanisms using examples used in the academic process within the course “Theory of Mechanisms and Machines”, which can be also successfully used within the design process, and includes examples of kinematic and dynamic analysis of linkage mechanisms, cam mechanisms, gear trains. In particular, the paper includes the simulation of the work process of the robot-manipulator using SOLIDWORKS Motion. It is shown that the usage of modern Computer-Aided Engineering systems (like SOLIDWORKS Motion or similar) enables to simplify the design process, shorten the design time and give an ability to carry out multi-parametric optimization procedures using different criteria, such as displacement values, velocities, accelerations, the values of reaction forces, overall dimensions etc. Besides, the usage of CAE-technologies enables to transform the academic process and makes it much more interesting or the students, who can use such technologies in their professional work in the future and become more competitive in the job market.

Solving Redundancy Allocation Problems using Jaya Algorithm

Reliability-based design is related to the performance analysis of engineering systems. The redundancy allocation problem is one of the most common problems in the reliability-based design approach. The redundancy allocation problem determines the redundancy level of components in a system to maximize system reliability, subject to several constraints. In recent years, obtaining solutions to reliability-related redundancy allocation problems by means of evolving meta-heuristic algorithms has appealed to researchers due to the several drawbacks of classical mathematical methods. Meta-heuristics have shown the potential of obtaining precise solution in optimization problems and many techniques have been applied in the literature for optimal redundancy allocation. In this paper, a recently developed Jaya optimization algorithm is proposed to be applied for redundancy allocation to maximize system reliability. The Jaya algorithm is a simple, population-based intelligent meta-heuristic algorithm consisting of a single phase and an algorithm-specific parameter-less algorithm. This paper aims to present an application of the Jaya algorithm for searching the optimal solution of two redundancy allocation problems from the literature with nonlinear constraints so that system reliability is maximized. The first problem is the over speed protection system for a gas turbine, whose control system is modelled as a four-stage series system. The objective is to determine the optimal level of redundancy of the valves of the protection system under cost and weight constraints. The second one is the redundancy allocation problem of a five-stage series system with volume, weight, and cost constraints. The results are validated by comparing them with two other meta-heuristics.