Engineering Case Study Research Articles

Multi-granularity feasibility evaluation method of the partial destructive disassembly for an end-of-life product

Partial destructive disassembly (PDD) is essential for end-of-life products to improve their automatic disassembly efficiency and reduce disassembly cost. A feasibility evaluation of the PDD is the key step to evaluate whether the PDD can be implemented. However, it has not been studied previously to our knowledge. To deal with this problem, a multi-granularity feasibility evaluation method is proposed. A multi-granularity feasibility evaluation model of the PDD was constructed based on the complex product’s hierarchical structure, which not only described the evaluation indices from the product level to the component level but also presented methods and rules to quantify them. Thus, disassembly entropy was introduced into the target group’s coarse granularity evaluation. The feasibility of the fine-grained index of the PDD for the component layer was constructed based on the product’s failure characteristic. The fine-grained index was calculated by the fuzzy trigonometric function, and its weighting was obtained based on the structure entropy weight method. Thus, the results of the evaluation were used as feedback to guide the PDD process. Finally, a Passat engine case study illustrates the feasibility and effectiveness of the method.

Plandemic Revisited: A Product of Planned Disinformation Amplifying the COVID-19 "infodemic".

During the first few months of the COVID-19 pandemic, a 26-min documentary entitled Plandemic was released online and fanatically shared via Twitter and other major social media platforms. The producers of the documentary sought to spread misinformation and conspiracy theories and to discredit scientific experts using a sophisticated disinformation campaign. They set out to accomplish this by coaching citizens toward activism to maximize the speed at which the documentary propagated and decrease positive sentiments toward public health interventions. Applying techniques from social network analysis in conjunction with a formative content analysis of Twitter data, we examined the effectiveness of the Plandemic disinformation campaign as a case study of social engineering during the COVID-19 pandemic. By comparing the Twitter network's community structure and communication patterns before and after the release of the film, we demonstrate the Plandemic campaign to have been effective for two reasons. First, the campaign established a decentralized information sharing network on Twitter by coaching low-reach social media users to mass share the documentary, effectively subverting efforts to gatekeep its misinformation. Second, the campaign amplified negative sentiments regarding vaccination and containment measures among conspiracy theorists. These effects possibly have an indirect impact on the public's willingness to comply with public health measures. Our results show the necessity of further research about sophisticated social experiments such as the Plandemic disinformation campaign and provide important insights for policy-making to combat the spread of health misinformation during public health crises.

On Shannon entropy computations in selected plasticity problems

AbstractThis paper considers the problem of determining probabilistic entropy fluctuations, which are important for understanding uncertainty propagation in mechanical systems in the elasto‐plastic regime. Probabilistic entropy is conceptualized based on an initial definition by Shannon, which demands discrete representation of the uncertainty source. Numerical analysis is performed using the Response Function Method with polynomial bases. Coefficients are found and order optimization is completed using polynomial interpolations or the Least Squares Method. Approximations are based on the Finite Element Method. Local polynomial bases enable nonlinear increment analysis, and allow for a given degree of freedom in the FEM model to be described as a function of a random input parameter. Academic FEM software and the ABAQUS system were used for numerical experiments. Polynomial approximations, probabilistic moment computations, and statistical entropy estimations were programmed in the symbolic algebra package MAPLE. Transformation of the input probability density into the output function was performed using the Monte‐Carlo simulation algorithm for statistically optimized polynomial bases of extreme displacement functions. Two computational examples are given to demonstrate probabilistic entropy fluctuations for a small statically indeterminate aluminum truss structure and also for practical engineering case study of the steel round bar under uniform tensile stress. In these examples, some material and geometrical uncertainties distributed according to Gaussian, triangular, uniform as well as lognormal distributions were analyzed. The presented approach could be used for constitutive models of solids, computational fluid dynamics, and in other discrete numerical methods.

Integration of Highly Skilled Migrants in the Workplace: a Multi-level Framework

This article combines literatures on immigrant integration and migration intermediaries to add a skilled perspective to theories of immigrant integration. Using a case study of foreign-born engineers in the Norwegian oil and gas industry, we develop a multi-level conceptual framework of actors that are involved in the integration of foreign-born engineers. We identified integration actors through in-depth, semi-structured interviews with human resource managers, foreign-born workers, and other integration actors. The framework is intended as a tool to move beyond single-level, unidirectional studies of immigrant integration and to provide a more in-depth understanding of the integration of highly skilled migrants in the workplace. We find that state actors fail to assist with the long-term integration for highly skilled migrants. Instead, private and voluntary actors provide information about work regulations and working life. In addition, employers and coworkers play an important role in the integration of highly skilled migrants in the workplace. We also find that highly skilled migrants can be agents of integration as they “scale up” initiatives to higher levels of decision-making.

Input‐response space‐filling designs

AbstractTraditional space‐filling designs are a convenient way to explore throughout an input space of flexible dimension and have design points close to any region where future predictions might be of interest. In some applications, there may be a model connecting the input factors to the response(s), which provides an opportunity to consider the spacing not only in the input space but also in the response space. In this paper, we present an approach for leveraging current understanding of the relationship between inputs and responses to generate designs that allow the experimenter to flexibly balance the spacing in these two regions to find an appropriate design for the experimental goals. Applications where good spacing of the observed response values include calibration problems where the goal is to demonstrate the adequacy of the model across the range of the responses, sensitivity studies where the outputs from a submodel may be used as inputs for subsequent models, and inverse problems where the outputs of a process will be used in the inverse prediction for the unknown inputs. We use the multi‐objective optimization method of Pareto fronts to generate multiple non‐dominated designs with different emphases on the input and response space‐filling criteria from which the experimenter can choose. The methods are illustrated through several examples and a chemical engineering case study.

The effect of mathematical matriculation as the basis for calculus lectures: a case study of electrical engineering, UNISNU Jepara - Indonesia

Mathematics is applied in all fields, 70% stated it is difficult, scary, and the survey results concluded that mathematics is a scourge for most students of all levels: Elementary School to College. Based on the results of the initial questionnaire student matriculation displeasure in mathematics starting in grade 3 elementary school, because arithmetic problems began to be difficult, the teacher was less familiar, dominant in learning and lacking in guidance, conditions tended not to change until high school. By matriculating researchers and acting as a lecturer, making the initial matriculation material as tension therapy, student anxiety in mathematics with a change in the mathematics mindset is fun, namely by using active and meaningful learning methods for students. With a growth mindset and meaningful learning, matriculation has implications for good mastery of students’ mathematical concepts.

African vultures optimization algorithm: A new nature-inspired metaheuristic algorithm for global optimization problems

Metaheuristics play a crucial role in solving optimization problems. The majority of such algorithms are inspired by collective intelligence and foraging of creatures in nature. In this paper, a new metaheuristic is proposed inspired by African vultures' lifestyle. The algorithm is named African Vultures Optimization Algorithm (AVOA) and simulates African vultures' foraging and navigation behaviors. To evaluate the performance of AVOA, it is first tested on 36 standard benchmark functions. A comparative study is then conducted that demonstrates the superiority of the proposed algorithm compared to several existing algorithms. To showcase the applicability of AVOA and its black box nature, it is employed to find optimal solutions for eleven engineering design problems. As per the experimental results, AVOA is the best algorithm on 30 out of 36 benchmark functions and provides superior performance on the majority of engineering case studies. Wilcoxon rank-sum test is used for statistical evaluation and indicates the significant superiority of the AVOA algorithm at a 95% confidence interval.

Passive noise control in buildings: An engineering case study of ducted systems

The most common noise sources in buildings are related to Heating, Ventilating and Air Conditioning (HVAC) systems, plumbing systems, electrical systems and exterior sources. Passive Noise Control (PNC) techniques in buildings have been implemented in several ways. The aim of this work is to analyses the use of silencer to attenuate the noise in the ducts that are part of the ventilation systems in buildings, internal combustion systems, fans, gas conduction systems, boilers, etc. The main objective of a silencer is to reduce the transmission of noise, disturbing as little as possible the circulation of gas or liquid. In the first instance, the silencers are classified as reactive and dissipative, depending on whether the attenuation of the noise is produced by reflective or dissipative mechanisms, respectively. In a reactive silencer, the losses occur essentially due to the reflections of the sound waves in impedance discontinuities, such as widening or narrowing of the tube. In dissipative silencers, the flow is in contact with a large surface of absorbent material. The attenuation of the noise is then produced by visco-thermal losses in the porous material. In this work, a practical issue will be addressed with a noise reduction of 19 dBA in 60 Hz. Practical application Noise is a current issue in residential areas that could lead to health problems for people. The origin of these noises within buildings is very diverse, one of them is produced by ducts. Appling the PNC technique in modern building construction would be a good prevention practice. For this reason, in this project a PNC system was carried out in the ducts of a residential building, which could be used as a praiseworthy solution, avoiding problems for the inhabitants of these spaces.

Identifying Multidisciplinary Metrics to Analyze NASA Case Studies

Background: Communication is fundamental to the success of engineered systems, enabling interactions between the system's stakeholders. Systems engineering, an integrative discipline on which the contributions of many disciplines are evaluated against each other, may particularly benefit from research in communication methods. Specifically, storytelling may be beneficial to engineers because it enables sense-making. Research into storytelling is conducted to identify storytelling metrics that could be useful in engineering communication, specifically engineering case studies. Literature review: Although storytelling has been identified in past research as possibly useful to Model-Based Systems Engineering (MBSE) and software requirement writing, a rigorous study of the use of storytelling elements in systems engineering communication has not been performed. Research question: How are storytelling elements currently being applied in engineering case studies? Research methodology: Twelve interdisciplinary metrics from storytelling, content analysis, and engineering are identified from the literature and used to characterize a collection of 48 NASA case studies. The values of the metrics for each case study are determined and analyzed using statistical and content analyses. Results and discussion: Analysis of the 12 metrics indicates that the case study design region with a historical backstory structure, climactic plot structure, and early points of attack is most frequently used by designers. Conclusions: The analysis indicates that certain storytelling elements applied in engineering case studies are used more frequently. Further work is needed to leverage the metrics as design variables in engineering case study writing.

A measurement model of project control systems success for engineering and construction projects case study: contractor companies in Saudi's petroleum and chemical industry

PurposeThe purpose of this paper is to presents a new modeling approach that provides a measurement tool for evaluating the effectiveness of Project Control Systems (PCS) and the improvement of the project control capability as a part of an organization's project management processes.Design/methodology/approachThis study used a project management maturity approach to develop a measurement model of PCS success. The key elements in this model have been identified using the Fuzzy Analytic Hierarchy Process (FAHP) method to analyze data from a case study involving contractor companies in Saudi's petroleum and chemical industry.FindingsThe results identified six critical elements for PCS success: (1) Change Management, (2) Earned Value, (3) Baselined Plan, (4) Resource Loaded, (5) Progress Method and (6) Governance Program. In addition, Project Forecasting and Corrective Action Verification were identified as the main areas where clients and contractors need to focus for the effective deployment of a PCS.Practical implicationsThe results of this study were used to create a PCS Maturity Model (PCSMM) and a PCS Success Index (PCSSI). The value of this index can help project managers to identify the maturity level of their PCS and improvement areas that lead to enhanced project performance.Originality/valueThis research presents an alternative maturity model for PCS assessment that provides a practical tool to identify areas for improving the critical elements of PCS success. The study draws a clear distinction between overall project success and the success of the PCS.

Within-Occupation Forms of Positional Labour Market Advantage in Three Skilled Occupations

In recent decades, many scholars have accentuated the role of occupations in social stratification and class analysis. Within occupations, workers compete to improve their labour positioning over time and in the process, create unequal outcomes. Advancement to better positions or improved wages can be dependent on many individual factors such as tenure, skills, experience, and effort. Yet, occupations also allow workers to create relative advantage by closing off opportunities to others or seeking otherwise meaningful distinction. This article aims to explain how the occupational context shapes how those within skilled occupations construct the means of relative labour market advantage. It is based on a wider UK case study of laboratory scientists, software engineers, and financial analysts. It shows that within each occupation, there are distinct forms of creating advantage depending on the nature of the occupation such as the educational composition of the incumbents, the situ of skill development, and the level of educational congestion within the occupation.

An uncertainty-based design optimization strategy with random and interval variables for multidisciplinary engineering systems

Generally, the traditional uncertainty-based multidisciplinary design optimization (UBMDO) methods are based on the probability distribution information of random design variables and parameters. However, the probability distribution information needs to be obtained based on a large number of sample points. In many engineering structure design problems, for some uncertainties, it is difficult to obtain enough experimental samples to construct their accurate probability distribution, only the variation interval of them can be known. In this situation, mixed uncertainties exist in the engineering systems. Furthermore, with the increase in the complexity of engineering systems, these mixed uncertainties will even produce cumulative effects along with the internal coupling of the systems themselves. To tackle these challenges, the random and interval variables (RIV) are considered and a strategy of UBMDO with RIV (UBMDO-RIV) is proposed in this study. In the given method, the evaluation of uncertainty constraints is performed in the worst case scenario due to interval uncertainties. Meanwhile, the classic decoupling strategy for UBMDO, the framework of sequential design and uncertainty evaluation (SDUE), is introduced into UBMDO-RIV to reduce the computational burden. The engineering case study is utilized to illustrate the application of the proposed strategy.

Re-engineering knowledge: a case study in pluralist conceptual engineering

ABSTRACT When fans of conceptual engineering discuss examples of their craft, they frequently focus on cases of ‘one-to-one’ conceptual engineering. That is to say, they focus on cases where a target pre-engineering concept is revised into, or replaced by, a single successor. The possibility that we might instead replace a suboptimal concept with multiple successors is, by contrast, comparatively underexplored. The goal of this paper is to defend this type of pluralist conceptual engineering as legitimate, and as a promising approach to unravelling certain traditional philosophical puzzles. I’ll do so largely by way of example, by exploring a preliminary application of the pluralist approach to one of the most notoriously recalcitrant targets of conceptual analysis: knowledge.

Mechanism and Procedure of Repeated Borehole Drilling Using Wall Protection and a Soft Structure to Prevent Rockburst: A Case Study

With the increasing mining depth of coal mines, the occurrence of rockburst, especially in mine roadways, is becoming critical as a severe dynamic disaster. This paper explores the stability control of deep mine roadways and solves the contradiction between the support and pressure relief of roadways by studying the use of an internal steel pipe for wall protection and a soft structure for energy absorption during repeated borehole drilling. Numerical simulations are performed to examine the effects of active support technology on the support structure during repeated drilling. Internal steel pipes can effectively prevent the support structure from being damaged. When the soft structure cracks, the energy transmitted from the rockburst to the roadway is significantly reduced. According to the deformation and failure characteristics of the surrounding rock of the 21170 roadway, the combination of anchor active support, hydraulic lifting shed support, and soft structure energy absorption is proposed. An engineering case study shows that the support method can effectively maintain the stability of the surrounding rock and ensure the safe mining of the working face. The proposed control method can provide reference for the prevention and control of rockburst in mine roadways under similar geological conditions.

Seismic Fragility Analysis of Base Isolated Structure Subjected to Near-fault Ground Motions

In order to better evaluate the performance of the base isolated structure under the near-fault earthquakes, this paper takes into consideration an existing engineering case study in China as the prototype, and uses OpenSEES platform to establish the nonlinear finite element model of the base isolated structure. The nonlinear response of the isolated structure under the near-fault earthquake is analyzed. The incremental dynamic analysis (IDA) method is used to calculate the damage probability of the structure under the near-fault earthquake, and the fragility curve of the base isolated structure is established. The fragility equation is obtained by nonlinear regression, and the error of fragility equation is analyzed. The results show that the maximum value of the inter-story drift of the upper structure under the action of near-fault earthquake is significantly greater than that under the action of far-fault earthquake. With the increase of seismic intensity, the damage probability of base isolated structure increases nonlinearly, and the maximum response value of horizontal displacement of bearing and inter-story drift of superstructure increases generally. In addition, the exceeding probability of the fragility curve based on PSDA is greater than that based on EDP criterion. When the sample points of the two methods are the same, the exceeding probability points calculated based on PSDA can be regarded as accurate values. The fragility curve based on PSDA may overestimate the exceeding probability to some extent, and the overestimation may be enlarged with the increase of failure stage.

Generating set search using simplex gradients for bound-constrained black-box optimization

The optimization problems arising in modern engineering practice are increasingly simulation-based, characterized by extreme types of nonsmoothness, the inaccessibility of derivatives, and high computational expense. While generating set searches (GSS) generally offer a satisfying level of robustness and converge to stationary points, the convergence rates may be slow. In order to accelerate the solution process without sacrificing robustness, we introduce (simplex) gradient-informed generating set search (GIGS) methods for solving bound-constrained minimization problems. These algorithms use simplex gradients, acquired over several iterations, as guidance for adapting the search stencil to the local topography of the objective function. GIGS is shown to inherit first-order convergence properties of GSS and to possess a natural tendency for avoiding saddle points. Numerical experiments are performed on an academic set of smooth, nonsmooth and noisy test problems, as well as a realistic engineering case study. The results demonstrate that including simplex gradient information enables computational cost savings over non-adaptive GSS methods.

Effect of Self-Study Component towards Students Performance in Chemical Engineering Coursework: Case Study of Chemical Engineering

Effect of Self-Study Component towards Students Performance in Chemical Engineering Coursework: Case Study of Chemical Engineering

Exploring gestural input for engineering surveys of real-life structures in virtual reality using photogrammetric 3D models

Photogrammetry is a promising set of methods for generating photorealistic 3D models of physical objects and structures. Such methods may rely solely on camera-captured photographs or include additional sensor data. Digital twins are digital replicas of physical objects and structures. Photogrammetry is an opportune approach for generating 3D models for the purpose of preparing digital twins. At a sufficiently high level of quality, digital twins provide effective archival representations of physical objects and structures and become effective substitutes for engineering inspections and surveying. While photogrammetric techniques are well-established, insights about effective methods for interacting with such models in virtual reality remain underexplored. We report the results of a qualitative engineering case study in which we asked six domain experts to carry out engineering measurement tasks in an immersive environment using bimanual gestural input coupled with gaze-tracking. The qualitative case study revealed that gaze-supported bimanual interaction of photogrammetric 3D models is a promising modality for domain experts. It allows the experts to efficiently manipulate and measure elements of the 3D model. To better allow designers to support this modality, we report design implications distilled from the feedback from the domain experts.

Quantitative Representation of Aleatoric Uncertainties in Network-Like Topological Structural Systems

Abstract The complex topological characteristics of network-like structural systems, such as lattice structures, cellular metamaterials, and mass transport networks, pose a great challenge for uncertainty qualification (UQ). Various UQ approaches have been developed to quantify parametric uncertainties or high dimensional random quantities distributed in a simply connected space (e.g., line section, rectangular area, etc.), but it is still challenging to consider the topological characteristics of the spatial domain for uncertainty representation and quantification. To resolve this issue, a network distance-based Gaussian random process uncertainty representation approach is proposed. By representing the topological input space as a node-edge network, the network distance is employed to replace the Euclidean distance in characterizing the spatial correlations. Furthermore, a conditional simulation-based sampling approach is proposed for generating realizations from the uncertainty representation model. Network node values are modeled by a multivariate Gaussian distribution, and the network edge values are simulated conditionally on the node values and the known network edge values. The effectiveness of the proposed approach is demonstrated on two engineering case studies: thermal conduction analysis of 3D lattice structures with stochastic properties and characterization of the distortion patterns of additively manufactured cellular structures.

Case Study Research in Software Engineering—It is a Case, and it is a Study, but is it a Case Study?

Case studies are regularly published in the software engineering literature, and guidelines for conducting case studies are available. Based on a perception that the label “case study” is assigned to studies that are not case studies, an investigation has been conducted. The aim was to investigate whether or not the label “case study” is correctly used in software engineering research. To address the objective, 100 recent articles found through Scopus when searching for case studies in software engineering have been investigated and classified. Unfortunately, the perception of misuse of the label “case study” is correct. Close to 50% of the articles investigated were judged as not being case studies according to the definition of a case study. We either need to ensure correct use of the label “case study”, or we need another label for its definition. Given that “case study” is a well-established label, it is probably impossible to change the label. Thus, we introduce an alternative definition of case study emphasising its real-life context, and urge researchers to carefully follow the definition of different research methods when presenting their research.