Engineering Case Study Research Articles

A new early warning Criterion for assessing landslide risk

A large number of engineering case studies have shown that the traditional early warning criteria, which evolved on the basis of displacement as a single piece of information, have many limitations in practical engineering. The displacement speed ratio (DSR) cannot determine the development trend of landslides due to the influence of periodic external environmental factors. Moreover, when landslides occur, the early warning system will have a false alarm due to the stepwise giant rise of landslides. To solve this problem, this paper proposes a new landslide warning criterion, the trend speed ratio (TSR), and also fuses TSR and DSR into a dual speed ratio method (DSRM) for judging landslide risk changes. We assess these methods by applying DSRM and DSR to 10 landslide cases, respectively. The results show that when TSR is greater than 2.0, the probability of landslide damage is high and when TSR tends to decrease, the landslide tends to be stable. For landslides that rise sharply in steps but are not damaged, DSR has a high false alarm rate, while DSRM can effectively reduce the false alarm rate. In terms of warning applicability, DSR can be applied in only half of the ten landslide cases studied, while DSRM is significantly more applicable. In addition, compared with the traditional method, the new method can determine the direction of landslide development and assess the risk of step-up landslides, providing new technical support for engineers engaged in landslide warning and control.

Genome-Scale Modeling and Systems Metabolic Engineering of Vibrio natriegens for the Production of 1,3-Propanediol.

The fastest-growing bacterium Vibrio natriegens is a highly promising next-generation workhorse for molecular biology and industrial biotechnology. In this work, we described the workflows for developing genome-scale metabolic models and genome-editing protocols for engineering Vibrio natriegens. A case study for metabolic engineering of Vibrio natriegens for the production of 1,3-propanediol was also presented.

Enhancing cooperative learning and student motivation with gamification strategies: A case study in industrial engineering

This contribution presents the pedagogical design of a subject through gamified activities supported by technological tools in which the integration of two key subjects of the Civil Industrial Engineering career were implemented, which are operational research and project evaluation. In addition, the results of the satisfaction and learning perception questionnaires administered at the end of the experience are presented. Gamification is planned and implemented as a collaborative learning strategy to relate knowledge and skills acquired in order to provide solutions to science-based engineering problems in the area of their profession. The experience has been developed with 10 students of the ninth semester of the 2017 generation of the career, dictated this semester. It should be noted that the course was planned to be taught in classroom mode, due to the COVID-19 pandemic, for both academics and students, it was a challenge and a learning achievement to teach the course online, since the University of Antofagasta was not prepared to teach classes in virtual mode. Even though Chilean universities have used gamification in engineering, there have been no records of the existence of subjects integrated with the application of this tool.The results obtained in this teaching innovation achieved motivation of our students, teamwork, learning to learn, good performance in the completion of academic activities and the satisfaction of students accredited through the survey.

A Novel Reliability Analysis Approach under Multiple Failure Modes Using an Adaptive MGRP Model

In this paper, a novel MRGP-SS method is proposed to deal with the reliability analysis problems under multiple failure modes. First, a random moving quadrilateral grid sampling (RMQGS) method is proposed to improve the randomness and uniformity of initial samples. Second, an adaptive procedure, which combines the multiple response Gaussian process (MRGP) model and the novel active learning functions, is proposed to efficiently and accurately produce surrogate models for failure surfaces. In this regard, two novel learning functions are introduced to adapt to different iterative cycles, one is employed to correct the quality of samples, and the other is used to search for the samples closest to the limit state surface. Third, the subset simulation (SS) is integrated into the adaptive MRGP model to estimate the failure probability under multiple failure modes with fewer function calls and time consumption. Numerical and engineering case studies are finally provided to demonstrate the effectiveness of the proposed method.

A Comparative Case Study of Engineers' Literacy Practices and Implications for Transformative Disciplinary Literacy Pedagogies in Engineering Education

ABSTRACTThe purpose of this comparative case study, conducted with eight engineers in different firms who specialized in different disciplines of engineering, was to identify and describe the patterned ways in which they used written genres in the context of object‐oriented activity, as well as to describe their evaluative frameworks and literacy practices. The research team used descriptive coding to analyze field notes from twelve two‐hour observations per engineer; they also used categorical thematic analysis to analyze transcripts from six interviews and retrospective protocols per engineer. The analyses indicated that, to some extent, engineers read and wrote distinct written genres that varied according to their role (e.g., quality assurance manager versus test designer) and the traditions of their discipline (e.g., electrical versus mechanical). However, across sites, roles, and disciplines, they used common evaluative frameworks when they evaluated texts’ accuracy, consistency, adherence to standards, currency, executability, reproducibility, concision, and clarity. In conjunction with these evaluative frameworks, engineers also enacted common literacy practices, such as cross‐checking, peer review, using templates when composing, and verifying with the physical world. The study concludes with implications for transformative, rather than reproductive, disciplinary literacy pedagogies in which students can use expansive disciplinary literacies in engineering to address issues that are important to them. As part of these pedagogies, students can articulate why common evaluative frameworks and literacy practices are important to producing safe outcomes in engineering, while they simultaneously expand these frameworks and practices to reflect values and cultures that are important to them.

Best Practices for Case Studies in Construction Engineering and Management Research

Best Practices for Case Studies in Construction Engineering and Management Research

Determining the critical buckling load of locally stiffened U-shaped steel sheet pile using dynamic correlation coefficient method

U-Shaped Steel Sheet Piles (USSSP) have buckling and bending problems during construction. In this research, the structural measure of stiffened plates applied along the longitudinal direction of USSSP is analyzed and proposed. A theoretical calculation method of stiffening effect is proposed based on the dynamic correlation coefficient method and the formula for the critical buckling load of locally stiffened USSSP is derived. A parametric analysis of the number, width, and arrangement scheme of the stiffened plates on the USSSP with different lengths is examined. The empirical formula derived for the total stiffening area and the critical load of the axial compression members of the USSSP is compared with practical results from an engineering case study. The results show a quadratic function under the condition of arranging the different number of stiffened plates at equal intervals, which is accurate in deriving the critical load values USSSP after local stiffening, and provide a theoretical basis for the optimization design of local reinforcement of USSSP axial compression members in engineering projects.

Performance of piezoelectric actuators in gas microvalves: An engineering case study

Microvalves used to control gas flow in water heaters are traditionally based on low cost ubiquitous solenoid technology. The demand for a better flux control and for reducing the dependence on the solenoid Cu and rare earth magnetic materials, underlines the need for alternative solutions. In this work we report an engineering case study with experimental validation where a substituting solution to a commercial heater solenoid microvalve is provided by a low-cost high stroke piezoelectric bender for gas flow control. We established the relations between applied voltages, bender displacements, gas pressure drops through the microvalve and associated flow rates and demonstrate that the operation conditions of the piezoelectric microvalve resemble those of the solenoid one. By manipulating the electrical potential difference applied to the bender it is possible to control the pressure drop associated with the microvalve. The piezoelectric microvalve behaves in a continuous mode, not as a on-off device, what is a significant advantage over the solenoid one. We have proven that it is possible to directly incorporate a piezoelectric bender in a commercial solenoid- driven microvalve without significant changes in the valve design. The resultant piezoelectric driven valve is faster, partial, high voltage but low current, and silent.

Investigation of Coal Preparation for Life Cycle by Using Building Information Modeling (BIM): A Case Study

Increasing the efficiency of coal preparation is the key link of mine production. This study proposed a framework of coal preparation for life cycle based on Building Information Modeling (BIM), in which the data resources can be retransmitted, and the integration of BIM application links has a high level. In this paper, the kappa big data processing architecture is used to realize the integration and unification of stream data and batch data processing process. By using deep learning method and multimodal data fusion method, the multimodal data association fusion is realized, and Bentley software is adopted for verification and integration. Taking a coal preparation plant as an engineering case study, the proposed framework is applied to build a big data subplatform of three-dimensional visual management. The following is suggested: (1) the three-dimensional visual review of the coal preparation online is realized, and the efficiency of the design results is improved; (2) the production and operation management of the coal preparation are carried out through the established platform, which indicated that the proportion of clean coal increased by 1.97%, and the average increase percentage for the total output is about 5.6%. Results from the case study show that the framework proposed in this study can provide efficient reference for coal washing in the coal preparation.

Constructing arguments in engineering student case studies

Student case studies in engineering have received little attention from English from Specific purposes researchers, in contrast to case studies in business, law and medicine. This article addresses this gap in an analysis of the rhetorical moves of student case studies in engineering. Drawing on Swales’s (1990) move analysis framework, the study found three obligatory sections: Introduction, Analysis and Recommendations. A total of eight moves within these sections are proposed, which writers use in building arguments concerning the recommendations they make. Drawing on background information, identifying problems and questions regarding the case, and employing conceptual frameworks, students analyse the cases from a variety of perspectives in order to make recommendations about the problems in the case. All eight of the proposed moves are found in multiple sections rather than being confined to a single section, a finding unusual in academic genres. A key contribution of this study is the fine-grained analysis of rhetorical moves and strategies within all case study sections. We anticipate that this analysis will benefit writing instructors teaching engineering students, as well as engineering instructors.

Bioinspiration of Product Architecture: Trading-Off System Effectiveness for System Robustness

Abstract This work analyzes the role of bioinspired product architecture in facilitating the design of robust engineering systems. Prior works have proposed design guidelines to facilitate the implementation of bioinspired product architectures for engineered systems. This work shows that implementing a bioinspired product architecture may improve a system’s robustness to random module failures, but may degrade the system’s effectiveness in the absence of any module failure. To demonstrate such a trade-off between the robustness and the undisrupted effectiveness of a system, this study quantitatively compares biological systems to their functionally equivalent modular systems. The modular equivalents of biological systems are first derived by utilizing Functional Modeling. The application of the bioinspired product architecture guidelines is then modeled as a transition from the modular product architecture of the modular equivalents to the actual product architecture of the biological systems. The effectiveness and the robustness of the systems are analyzed after the application of each guideline by modeling the systems as multi-flow directed networks. Such an analysis is performed by introducing metrics that quantify a system’s expected effectiveness and the degradation in the system’s expected effectiveness with increasing severity of random disruptions. The findings are validated by designing and analyzing a COVID-19 breathalyzer as an engineering case study.

Central Load-Bearing Control in the Construction Process of the Concrete Spherical Joint Nandu River Swing Bridge: A Case Study

The rotating mechanism is a significant procedure in swing bridges. In this paper, the Nandu River swing bridge is taken as an engineering case study to exhibit the critical technology of the monitoring process and the construction method of the swing bridge. The research focuses on the central load-bearing control system used to guarantee the security of the construction process. The mechanical problems during the construction process are discussed. Simultaneously, the cable tension and gravity center test are introduced. The non-Hertz contact theory is utilized to calculate the stress distribution of the spherical joint. Furthermore, the overturning moment is computed to monitor the stability of the rotating system based on the stress distribution calculation of the spherical joint. The monitoring process of central load-bearing control is entirely exhibited and discussed. Concurrently, the calculating result of the real-time overturning moment reflects the stability of the rotating construction process, and adjustments are made to ensure the safety of construction. The results show that, during the cable tension process, the middle position of the main arch exhibited 162.3 mm maximum vertical displacement. Meanwhile, the fraction moment was greatly larger than the unbalanced moment. Furthermore, the maximum overturning moment value was 2094.38 kN·m, which was smaller than the resistance of the overturning moment. The present research demonstrates that the non-Hertz contact theory fits the calculation of spherical joint stress distribution. Simultaneously, the middle position of the main arch should be monitored to control the vertical displacement at the cable tensioning stages. The gravity center test and stability control of the rotating construction are the key steps to reaching central load-bearing control.

Covariance matrix adapted grey wolf optimizer tuned eXtreme gradient boost for bi-directional modelling of direct metal deposition process

The process of direct metal deposition for cladding has become extremely popular. Online condition monitoring of the process is necessary to obtain a desired clad geometry. The aforementioned fact has necessitated the development of accurate predictive models for establishing relationships between the input and the output parameters of the process in a bi-directional fashion. The present study attempts to build both forward and backward models of a direct deposition process of austenitic steel utilizing the extreme gradient boost technique. Inspired by the successful application of grey wolf optimization algorithm in solving real life problems, the authors further propose a novel modification of the same and use it to tune the parameters of the model with an aim to improve its performance. The improvement has been accomplished by changing the initial perspective prey location guided by the covariance matrix adaptation and recombination. The new optimization algorithm has been tested and compared with the original algorithm along with some of its variants and several other state-of-the-art meta-heuristics on 23 benchmark objective functions from literature and 5 from CEC 2017. The new optimizer has been further validated on some real engineering case studies. The developed hybrid models for bi-directional mappings using different optimizer turn-by-turn have been trained and tested using statistically augmented experimental data-set. The overall mean absolute percentage errors in testing forward mapping and backward mapping using the model with new optimizer have been found within 10%, which is quite satisfactory. The adequacy of the developed models has also been found acceptable.

Comparative analysis of model‐based and traditional systems engineering approaches for simulating a robotic space system architecture through automatic knowledge processing

AbstractModel‐based Systems Engineering (MBSE) case studies in the literature assert that there are benefits to MBSE when applied to modeling and simulating space systems. This research evaluates the benefits of an MBSE modeling and simulation approach over a traditional, non‐MBSE approach through modeling and simulation of an orbiting sample Capture and Orient Module (COM) architecture for potential Mars Sample Return (MSR). The COM architecture was modeled, simulated, and evaluated against nominal load power and output data rate requirements to compare the two approaches. A new modeling and simulation‐centric V‐model was synthesized from existing V‐model and modeling and simulation process models to map out the modeling and simulation activities within the context of the system development lifecycle and used as a tool to compare the non‐MBSE and MBSE approaches. A three‐phase modeling and simulation process consisting of an analysis and modeling phase, computer programming and implementation phase, and experimentation phase was used to model and simulate the COM. The total number of manual and automatic knowledge processed was calculated for both approaches and used to quantify the benefits of the MBSE approach relative to the non‐MBSE approach. In the non‐MBSE approach, all knowledge elements were manually processed during the modeling and simulation process. In the MBSE approach, 49% of total knowledge processing was automated. The MBSE approach showed user experience benefits with modeling and simulating the COM robotic space system through providing a higher level of support for automation, reducing the burden of systems engineering tasks, and reducing effort.

Bayesian Mass Averaging in Rigs and Engines

Abstract This paper introduces the Bayesian mass average and details its computation. Owing to the complexity of flow in an engine and the limited instrumentation and the precision of the sensor apparatus used, it is difficult to rigorously calculate mass averages. Building upon related work, this paper views any thermodynamic quantity’s spatial variation at an axial plane in an engine (or a rig) as a Gaussian random field. In cases where the mass flowrate is constant in the circumferential direction but can be expressed via a polynomial or spline radially, this paper presents an analytical calculation of the Bayesian mass average. In cases where the mass flowrate itself can be expressed as a Gaussian random field, a sampling procedure is presented to calculate the Bayesian mass average. Examples of the calculation of the Bayesian mass average for temperature are presented, including with a real engine case study where velocity profiles are inferred from stagnation pressure measurements.

Reduction of Petri net maintenance modeling complexity via Approximate Bayesian Computation

The accurate modeling of engineering systems and processes using Petri nets often results in complex graph representations that are computationally intensive, limiting the potential of this modeling tool in real life applications. This paper presents a methodology to properly define the optimal structure and properties of a reduced Petri net that mimic the output of a reference Petri net model. The methodology is based on Approximate Bayesian Computation to infer the plausible values of the model parameters of the reduced model in a rigorous probabilistic way. Also, the method provides a numerical measure of the level of approximation of the reduced model structure, thus allowing the selection of the optimal reduced structure among a set of potential candidates. The suitability of the proposed methodology is illustrated using a simple illustrative example and a system reliability engineering case study, showing satisfactory results. The results also show that the method allows flexible reduction of the structure of the complex Petri net model taken as reference, and provides numerical justification for the choice of the reduced model structure.

Guiding legacy systems for evolution. PmatE: a case study of maintenance and engineering

Even though software change is inevitable, accurate maintenance can extend software lifespan in a subtle way when both budget and time constraints get in the way of software replacement. In the University of Aveiro, the project PmatE – a quiz web platform created to encourage students to like Math – emerged in the early 1990’s and stacked several applications over the decades without major planning, cleaning or upgrade. This resulted in a huge-sized framework that was crucial to be always available and online and had high operational cost, leading to an increasing amount of technical debt. After 3 decades, the project was studied, refactored and refurbished, leading to a stable consistent framework ready for evolution and software spinouts. This work shows how to manage and engineer solutions to maintain a legacy system and evolve it even when tied up to heavy constraints.

A Case Study of Domain Engineering in Software Product Line Engineering

A Case Study of Domain Engineering in Software Product Line Engineering

Case Study of Sustainable Engineering by Using Computational Design

Case Study of Sustainable Engineering by Using Computational Design

ParaHydro: A Parallel System for Hydraulic Engineering

This paper introduces the applications of Parallel Intelligence to hydraulic engineering. A software is developed based on Blender to support the ACP framework, i.e., construction of Artificial models, carrying out Computational experiments, and Parallel execution. Based on the framework, two case studies in hydraulic engineering on a dam and a slope respectively are descripted briefly, including the main steps of modelling, simulating and executing. The applications verified that the paradigm of parallel intelligence works well in practice.