Unified Finite Element Method for Engineering Systems with Hybrid Uncertainties

Integrating Core Systems Engineering Design Concepts into Traditional Engineering DisciplinesIn this study we describe the integration of core systems engineering design concepts intotraditional mechanical and electrical engineering curriculum at the University of Arkansas atLittle Rock (UALR) undergraduate Systems Engineering program. The program was launched in1999 in response to the industry demands for engineering graduates capable of managingcomplex engineering projects. The program has since graduated over 150 students who areworking in industry (aerospace, defense, manufacturing, design, and consulting), federal andstate government, or attending graduate school. The program curriculum has four broadcomponents: a 35 hour university core that covers basic math and science (11 hours) and generaleducation (24 hours); a 30 hour college core that enhances the math and science preparation witha course in engineering ethics; a 32 systems engineering component that introduces core systemsengineering concepts; and, a 32 hour option component that teaches the mechanical or electricalengineering disciplines. The program is accredited by ABET under general criteria, and plans areunderway to satisfy mechanical and electrical engineering program criteria. Students entering theprogram are introduced to systems engineering core concepts through courses in EngineeringEconomy, DES Modeling and Simulation, Optimization Methods, Decision and Risk Analysis,and Systems Engineering Design and Analysis. Among them, Engineering Economy coversengineering project evaluation and economic decision making. Optimization Methods in SystemsEngineering covers linear and nonlinear methods of engineering design optimization. DESModeling and Simulation covers theory and practice of discrete event simulation modeling.Decision and Risk Analysis covers uncertainty modeling and analytical techniques for rationaldecision making. Systems Engineering Design and Analysis covers the systems engineering life-cycle process, including identification of system requirements, engineering design andarchitecture, system modeling, testing and integration, and system operation and support. The128-hr program culminates in a two-semester Systems Engineering Capstone Design thatemphasizes the multi-disciplinary nature of the program. The students perform functional designin the first semester followed by detailed physical design and testing in the second semester. TheUALR program graduates skilled systems engineers who combine holistic thinking with deepproduct knowledge, strong technical background, effective communication skills, and goodinterpersonal skills.

Computational methods, such as the finite element method, are nowadays necessary for the analysis and design of large-scale engineering systems. The considerable influence of inherent uncertainties on system behavior has also led the scientific community to recognize the importance of a stochastic approach to engineering problems. Engineering experience has shown that uncertainties are involved not only in the loading but also in the material and geometric properties of engineering systems. The rational treatment of these uncertainties cannot be addressed rigorously in the framework of the traditional deterministic approach. Stochastic methods do provide this possibility at the expense of increasing the complexity of the system model and, consequently, of the required computational effort for the solution of the problem. Therefore, the exploitation of the available computational resources and the development of enhanced solution algorithms are of paramount importance in the application of stochastic methods to real-world problems and to their further dissemination to the engineering community. The problems of response variability and reliability of structures with stochastic properties under dynamic loading are currently the subject of extensive research in the fields of computational stochastic dynamics and earthquake engineering. Both problems deal with the computation of the statistical characteristics of the response (statistical moments, probability of failure), and their solution is time consuming, particularly in the case of large-scale realistic structures. An important practical application of structural response variability and reliability is the estimation of seismic fragility curves used to assess the vulnerability of structures due to earthquakes. Fragility curves provide the probability of exceeding a prescribed level of damage for a wide range of ground motion intensity, usually expressed in terms of peak ground or spectral accelerations. The existing analytical methods for the evaluation of structural response variability and reliability can only be used in few special cases and are not applicable to realistic engineering problems. Therefore, this chapter will be focused on approximate methods and simulation. The first class of methods is mostly based on the approximation of the underlying Fokker–Planck–Kolmogorov equation or of the limit state function, while the second comprises the direct Monte Carlo simulation and its variants. In sections “Response Variability of Stochastic Systems” and “Reliability of

Strategic Environmental Assessment (SEA) Process towards the Sustainable Design and Construction of Computer, Communication, Network Engineering, Machine Learning and Artificial Intelligence Systems

The design of complex engineering systems often relies on simulation-based models, which inherently introduce uncertainty. Consequently, effective system design necessitates the incorporation of robust design principles and metrics to manage the uncertainties. From a decision-based design perspective, metrics such as the Design Capability Index (DCI) and Error Margin Index (EMI) are employed in problem formulations to address this challenge. These metrics typically utilize Taylor series-based approximations to estimate variance. However, due to the structural limitations of the Taylor series expansion, these formulations may mislead designers toward local minima rather than guide them toward actual robust solutions. In this paper, we propose an alternative formulation of the Design Capability Index (DCI) and Error Margin Index (EMI) that leverages the multiple-point variance estimation method. This approach employs a weighted average of multiple points to assess variance estimations around the nominal design, ensuring that the solution is not confined to a local optimum by estimating the correct variance at the local optimum. The proposed alternative metrics are incorporated into the robust Concept Exploration Framework (rCEF) to find robust solutions for complex engineering systems. A machine learning-based visualization tool, the interpretable Self-Organizing Maps (iSOM), is used to visualize and explore the high-dimensional robust solution space generated using the updated rCEF. Two examples are used to evaluate the proposed formulation: (i) a polynomial function to examine the effect of the alternative variance estimation method on EMI and DCI metrics, and (ii) a comprehensive hot rod rolling problem, considering model parameters and model structure uncertainty.

Rapid turn-around time for investigating new design concepts is a primary force driving design productivity initiatives across the industry. An integration framework focusing on the collaborative nature of rapid design automation at the preliminary and detailed design stage would ensure higher quality designs from the beginning of the product design cycle. As a result, producing reliable, robust optimum designs from the preliminary design phase would enable companies to reduce the overal design cycle time.

<p>La participación en una sociedad cada vez más tecnológica hace que se planteen numerosos interrogantes sobre la protección de los sujetos más vulnerables, entre ellos los menores. La influencia de las redes sociales como instrumento de comunicación no está exenta de riesgos por la cantidad de información que se facilita y se comparte.</p><p> La falta de una regulación específica que contemple desde el punto de vista del Derecho cuál es la protección que un menor debe tener, hace que se produzcan situaciones de desamparo de los derechos de los mismos.</p><p> La oportunidad de regulación se ha dejado escapar en la futura ley de protección de la infancia, actualmente en fase de anteproyecto, ya que no hace referencia a las redes sociales como hubiera sido deseable. Las normas actuales en materia de menores, así como las de protección de datos, entre otras, no resultan suficientes para contemplar todas las situaciones de riesgo que pueden darse en dicho ámbito.</p><p> En el presente trabajo nos proponemos reflexionar sobre menores y redes sociales planteando algunas cuestiones legales, e intentando aportar alguna respuesta a la problemática que se plantea en el ámbito jurídico.</p>

The main aim of this paper was to propose a new reliability index for steel structure assessment and to check it using the example of a popular Pratt truss girder. Structural analysis was completed in the finite element method system Autodesk ROBOT, and probabilistic analysis was implemented in the computer algebra software MAPLE. The stochastic finite element method (SFEM) was contrasted here with the Monte Carlo simulation and the girder span was selected as the input structural uncertainty source. Both methods were based on the same structural polynomial response functions determined for extreme deformation, for extreme stresses and also for the structural joint exhibiting the largest effort. These polynomials were statistically optimized during the additional least squares method experiments. The first four basic probabilistic characteristics of the structural responses, the first-order reliability method (FORM) index, and as the new proposition for this index were computed and presented. This new index formula follows the relative probabilistic entropy model proposed by Bhattacharyya. The computer analysis results presented here show a very strong coincidence of both probabilistic numerical techniques and confirms the applicability of the new reliability index for the input coefficient of variation not larger than 0.15. These studies should be continued for other engineering systems’ reliability and, particularly, for large-scale and multiscale computer simulations. The results presented in this paper may serve in different applied sciences, from biology through to econometrics, experimental physics and, of course, various branches of engineering.

The point-based approach consists of committing a set of requirements and a single design solution from the design space. This approach is time-consuming and often leads to deadline excess when developing a new complex system such as mechatronic systems. In fact, this approach could generate iterative loops between engineers in the downstream design stage to evaluate the manufacturability and the quality of the developed system. To overcome this issue, introducing a model-based system engineering (MBSE) approach in the upstream design stage hinged on set-based concurrent engineering (SBCE) principles is a good solution to diminish the exchange loops between engineers and to enhance efficiency in the design process. This approach consists in evaluating a large set of system solutions, then gradually narrowing these solutions until converging to a limited set of optimized solutions. In this article, a novel approach entitled “Model based for reliability and manufacturability analysis (MBRMA)” and based on model-based system engineering and set-based concurrent engineering in the preliminary design phases is used to filter out weak or costly solutions over time and to assess system engineer when adopting trade-off analysis. First, customer requirements, functional and structural aspect of the system are defined using SysML diagrams. Next, the application of the algorithm allows narrowing the design space, and finally, a trade-off analysis is carried out to select the best system architecture. The first contribution of this article is the creation of novel stereotypes of composition and allocation flows in a profile diagram between functions and alternative solutions. The second contribution is the implementation of an algorithm to analyze system robustness and to converge on the final set of optimized solutions. To test this newly developed model “model based for reliability and manufacturability analysis (MBRMA),” a case study of an air conditioning electrical compressor is considered to illustrate the various stages of this concurrent engineering approach.

Beech 1900D flight test to characterize propeller noise on the fuselage exterior

Graphite components serve as structural support and as a neutron moderator in multiple nuclear power stations and is also a prospective material in Generation IV reactor concepts. The environment (e.g. high temperature and intense radiation) within a graphite core changes the geometry, microstructure and material properties of the graphite components, that could limit the lifetime (i.e. safe operation) of a reactor. Some of the assessments made for graphite reactor core components include Finite Element Method (FEM) simulations. These simulations are used to estimate the stress state and strain state and probability of failure of irradiated graphite components. FEM also forms part of the validation of measurements or as a complementary technique to experimental procedures in graphite research. A comprehensive overview of FEM methodologies is provided in this review, including: FEM software, basics steps to set up a FEM model, and analytical solutions used to validate simulations for this field of study. The objective of this paper is to inform researchers in the different available FEM techniques and tools used in the research of nuclear graphite.

In the present study, a scheme based on fuzzy finite element method was provided for uncertainty quantification of liquefied saturated soil response under dynamic loading. In this respect, the coupled dynamic equations which are known as u-p equations were used, and instead of crisp values for input parameters, including permeability coefficient, specific mass of the soil, compressibility and shear modulus, their fuzzy numbers were used. At the end, displacements and pore water pressure created during earthquake were reported as fuzzy numbers. After verifying procedures of fuzzy analysis by experimental results from the centrifuge model test No. 1 from the VELACS project, several membership grades were considered. Firstly, the effect of fuzzification of each input soil parameter investigated individually, and then effect of considering all four input soil parameters as fuzzy numbers was analyzed by developed method. It was indicated that results of the analysis during the effective time of the earthquake were strongly influenced by the shear modulus and partially by compressibility modulus, and after this time, it was mainly affected by the permeability coefficient. Also considering uncertainty nature of specific mass of the soil had no significant effect on the results.

Contributors

The lifespan of a reinforced concrete (RC) structure can be greatly influenced by the spatial variability of its material characteristics which, in particular, explains the observed or measured reduction of the tensile strength at first crack when the volume under tension increases. This paper discusses the ability of accounting for the spatial variability of the tensile strength of concrete in RC structures using a stochastic finite element (SFE) method based on random field simulations. In this work, the generation of random fields on the concrete tensile strength aims at computing the force corresponding to the first crack occurrence, and the reduced tensile strength of the structure. The method can be applied in particular to large‐sized structures, which show a pronounced size effect, for different types of loading. The method consists of, first, estimating the mean of the random field, using the analytical approach of the weakest link and localization method (WL ). Then, the discretized random field is defined on a particular 2D or 3D grid, and it is finally projected on the finite element mesh of the studied structure. The study of the parameters that influence the prediction of the cumulative density functions (CDFs) of the rupture force or the tensile strength is highlighted using experimental series of concrete beams having different volumes and subjected to 4‐point bending loading. Moreover, the SFE method is applied to a RC tie‐beam under tensile loading, characterized by a weak stress gradient, which complicates the prediction of crack positions.

Under the complex operational environment of the antimissile operation, the application of Systems Modeling Language (SysML) parametric model in weapon system effectiveness evaluation is explored. The function of parametric graph model, the construction process of the model and the optimization method of the model are researched. Using feedback mechanism to collect, collate and calculate the parameters of the model, and realize the leap from the index relationship description to the calculation of the index. Finally, the feasibility and effectiveness of the proposed method is verified by using the system of antimissile weapon system as an example.

We hypothesize that by providing decision support for designers in industry we can speed up the design process and facilitate the creation of quality cost-effective designs. One of the challenges in providing design decision support is that the decision workflows embody various degrees of complexity due to the inherent complexity embodied in engineering systems. To tackle this, we propose a Knowledge-Based Platform for Decision Support in the Design of Engineering Systems (PDSIDES). PDSIDES is built on our earlier work that is anchored in modeling decision-related knowledge with templates using ontology to facilitate execution and reuse. In this paper, we extend the ontological decision templates to a computational platform that provides knowledge-based decision support for three types of users, namely, Template Creators, Template Editors, and Template Implementers, in original design, adaptive design, and variant design respectively. The efficacy of PDSIDES is demonstrated using a Hot Rod Rolling System (HRRS) design example.