Large Engineering Research Articles

Uncertainty Quantification of Locally Nonlinear Dynamical Systems Using Neural Networks

Models are often given in terms of differential equations to represent physical systems. In the presence of uncertainty, accurate prediction of the behavior of these systems using the models requires understanding the effect of uncertainty in the response. In uncertainty quantification, statistics such as mean and variance of the response of these physical systems are sought. To estimate these statistics, sampling-based methods like Monte Carlo often require many evaluations of the models’ governing differential equations for multiple realizations of the uncertainty. However, for large complex engineering systems, these methods become computationally burdensome as the solution of the models’ governing differential equations for such systems is expensive. In structural engineering, an otherwise linear structure often contains spatially local nonlinearities with uncertainty present in them. A standard nonlinear solver for them with sampling-based methods for uncertainty quantification incurs significant computational cost for estimating the statistics of the response. To ease this computational burden of uncertainty quantification of large-scale locally nonlinear dynamical systems, a method is proposed herein that decomposes the response into two parts: response of a deterministic nominal linear system and a corrective term. This corrective term is the response from a pseudoforce that contains the nonlinearity and uncertainty information. In this paper, neural network, a recently popular tool for universal function approximation in the scientific machine-learning community due to the advancement of computational capability as well as the availability of open-source packages, is used to estimate the pseudoforce. Since only the nonlinear and uncertain pseudoforce is modeled using the neural networks, the same network can be used to predict a different response of the system, and no new network is required to train if the statistics of a different response are sought.

Predicting Tbm Performance for Pila Spi Formation in Qara Dagh Anticline, NE Iraq

There are a few studies on the engineering properties of the Pila Spi Formations in scattered areas of Northern Iraq, but there is no study on predicting the performance of Tunnel Boring Machines (TBM), which is of great importance in future large engineering projects in Iraq. The study area is located on the Takya about 50 km south the center of Sulaimania City. Field and laboratory studies were conducted on five (5) selected sites situated in the southwestern flank of the Qara Dagh anticline. The axis of the anticline extends from NW-SE of Iraq with a length of roughly 116 km. The engineering and field results of the samples collected from different locations indicate that the compressive strength of the rocks having a fine texture and slightly weathered characteristics ranges between strong to very strong with high dry density and low moisture content. In addition, the average Schmidt hammer rebound and weight losses percentages of Lose Angeles values are 48 and 22%, respectively the sizes of the blocks range from large to very large, the spacing of the discontinuities is medium to wide. The performance of TBM in terms rate of advance is generally determined based on these geological rock materials and masses. To estimate the rate advance of boring machine (TBM) in this study, the method depends on the total hardness. After applying the total hardness method, it was estimated that the predicted rate of advancement of the TBM would be very slow (approximately 1.57 -1.86 m/hr) due to the strong hardness of the rocks of Pila Spi Formation.

An Empirical Study of Delays in Large Engineering Projects: An Indian Experience

This article analyzes factors responsible for delays in two large projects undertaken by an Indian organization over a period of 7 years. The research work critically examines the reasons for delays using questionnaires in four core areas of project work. An in depth analysis has identified 10 factors, which cause delays, viz., inept project planning practices, inadequate and inexperienced consultant personnel, recurring stakeholders interactions, incomplete understanding of the client’s requirements, unfamiliarity with documentation needs in the client country, subsequent client and inspection agency-driven change requirements, incomplete preparation at the hook-up yard, and delays in vendor mobilization/inadequate vendor expertise. The original contribution of this research is in the areas of analyzing and understanding delays due to doing work in offshore locations, doing project management work using documents in offshore country language, understanding offshore country laws and regulations, in-depth understanding of the root causes of delays using detailed, segmented questionnaires and analysis of the sequential nature of project management work.

Mathematical model of turbofan engine weight estimation taking into account the engine configuration and size

The paper presents a new correlation-regression model of estimating the turbofan engine weight considering the effect of the engines design schemes and dimensions. The purpose of this study was to improve the efficiency of the conceptual design process for aircraft gas turbine engines. Information on 183 modern turbofan engines was gathered using the available sources: publications, official websites, reference books etc. The statistic information included the values of the total engine air flow, the total turbine inlet gas temperature, the overall pressure ratio and the bypass ratio, as well as information on the structural layout of each engine. The engines and the related statistics were classified according to their structural layout and size. Size classification was based on the value of the compressor outlet air flow through the gas generator given by the parameters behind the compressor. Depending on the value of this criterion, the engines were divided into three groups: small-sized, medium-sized gas turbine engines, and large gas turbine engines. In terms of the structural layout, all engines were divided into three groups: turbofan engines without a mixing chamber, engines with a mixing chamber and afterburning turbofan engines. Statistical factors of the improved weight model were found for the respective groups of engines, considering their design and size. The coefficients of the developed model were determined by minimizing the standard deviations. Regression analysis was carried out to assess the quality of the developed model. The relative average error of approximation of the developed model was 8%, the correlation coefficient was 0,99, and the standard deviation was 10,2%. The model was found to be relevant and reliable according to Fisher's test. The obtained model can be used to assess the engine weight at the stage of conceptual design and for its optimization as part of an aircraft.

Engine Malfunctioning Conditions Identification through Instantaneous Crankshaft Torque Measurement Analysis

In this study a coupled thermodynamics and crankshaft dynamics model of a large two-stroke diesel engine was utilised, to map the relationship of the engine Instantaneous Crankshaft Torque (ICT) with the following frequently occurring malfunctioning conditions: (a) change in Start of Injection (SOI), (b) change in Rate of Heat Release (RHR), (c) change in scavenge air pressure, and (d) blowby. This was performed using frequency analysis on the engine ICT, which was obtained through a series of parametric runs of the coupled engine model, under the various malfunctioning and healthy operating conditions. This process demonstrated that engine ICT can be successfully utilised to identify the distinct effects of malfunctions (c) or (d), as they occur individually in any cylinder. Furthermore by using the same process, malfunctions (a) and (b) can be identified as they occur individually for any cylinder, however there is no distinct effect on the engine ICT among these malfunctions, since their effect on the in-cylinder pressure is similar. As a result, this study demonstrates the usefulness of the engine ICT as a non-intrusive diagnostic measurement, as well as the benefits of malfunctioning conditions mapping, which allows for quick and less resource intensive identification of engine malfunctions.

Ultrafine-grained dual-phase maraging steel with high strength and excellent cryogenic toughness

A novel heat treatment route consisting of a low-temperature solution followed by an over-aging treatment at 500 °C is proposed to develop a high-strength, high-cryogenic-toughness maraging steel by forming an ultrafine-grained martensite (α′) and austenite (γ) dual-phase microstructure. Compared to the same maraging steel subjected to the conventional heat treatment with a mostly martensitic microstructure, the present dual-phase microstructure offers a remarkable increase by 12 times of cryogenic impact energy (~140 J at 77 K), while the yield strength is not reduced obviously. A large amount of ultrafine-grained austenite (about 50% volume fraction) are formed in the present steel due to the reversed transformation of martensite to austenite during the over-aging process at 500 °C. It is surprised that the present steel with such a high fraction of austenite still possesses a high yield strength comparable to the conventional maraging steel with a mostly martensitic microstructure. Intensive nanoprecipitates are found not only in martensite but also in austenite phases, indicating both phases have high strength. This is confirmed by nanoindentation test, showing similar hardness values in both martensite and austenite phases. Such intensive nanoprecipitates in both phases ensure the high yield strength of the present steel. The excellent cryogenic toughness of the present steel mainly origins from: (i) the pronounced amount of reversed austenite that are intrinsically tough due to their face-centered cubic (fcc) structure; (ii) transformation-induced plasticity (TRIP) toughening as some austenite grains transforming to martensite during impact test; (iii) the ultrafine-grained structure of both martensite and austenite phases. The present heat treatment route offers a potential solution for processing large engineering components for cryogenic application that require a long heat treatment duration to achieving uniform mechanical properties in the components.

The importance of equation η = μn 2 in dimensional analysis and scaled vehicle experiments in vehicle dynamics

Dimensional analysis has been very helpful in experimentation of very large or small-scale engineering systems. A good example would be experimentation on the aircrafts and ships, which was made cost-effective and simple by dimensional analysis. The history of dimensional analysis mentioned in the introduction section of the present document includes many of such applications. Automotive industry, however, never felt the need as the price or the size of land vehicles did not make experimentation so far-fetched; therefore, there are many crash tests which every new vehicle has to go through before mass production This changed with the imminent introduction of autonomous vehicles, which brought all the risks involved in experimenting with them. Many cost-effective experimental platforms are introduced, such as QCar https://www.quanser.com/products/qcar/ or laboratories, such as Scaled Autonomous Vehicles Indoor (SAVI) https://cast.tamu.edu/research/technology-demonstrator-platforms/scaled-autonomous-vehicles-indoor-tdp/. The present study will enable the results taken from such platforms to be translated to real-sized vehicles, enabling researchers to study dynamics of various vehicles. Classical vehicle equations of motion including constant velocity, accelerating bicycle model and roll model have been made dimensionless. The case of steady-state responses is also calculated in a dimensionless form. Some practical numerical examples are also mentioned as a proof of theory.

Development of common rail lube oil injector for large two-stroke marine diesel engines

The two-stroke crosshead diesel engines, nowadays moving the majority of merchant vessels, have lubrication systems which significantly contribute to their overall emissions, since they work on total loss basis: a relevant fraction of lubricant enters the exhaust duct, increasing total exhaust emissions. This paper demonstrates that a viable solution to reduce lubrication system related emissions can be found in the application of a new common rail type ( CR) lubrication system. Particularly, in the first part of this study, a common rail injector was simulated and numerically optimized by means of AMESim. The main parameters influencing lube oil injected mass were identified, with the purpose to design a highly time responsive injector. Therefore, a CR injector was realized and experimentally characterized by means of a dedicated test cell, defining the lube oil injection map over the entire engine load range. Finally, full scale engine tests allowed to evaluate oil loss at exhaust, proposing, and applying the Sulfur tracing methodology. A comparison with a pulse jet lubrication system demonstrated a relevant reduction in oil loss: 100% engine load testes demonstrated decreases ranging from 56.2% to 63.3%, while once fixed the lube oil feed rate to 0.8 g/kWh a maximum reduction in oil loss equal to 66.7% was reached. These results allow nominating the common rail lubrication system as a feasible solution to significantly reduce oil loss at exhaust of large two-stroke marine diesel engines.

Industrial and Large Engines

Industrial and Large Engines

Spectral variational multiscale enrichment method—A new computational approach to transient dynamics of phononic crystals and acoustic metamaterials

Phononic crystals and acoustic metamaterials hold tremendous potential in controlling mechanical and acoustic waves, thereby enabling remarkable and novel engineering applications such as seismic wave mitigation, impact wave mitigation, elastic cloaking, and acoustic superlens. Given the potential complexity associated with the microstructure of these materials, direct numerical simulation of irregularly shaped and/or large engineering components could be computationally very costly and in many cases prohibitive. Multiscale computational modeling, coupled with model order reduction methodologies present a feasible strategy to simulate the dynamic response of phononic crystals and acoustic metamaterials. In this study, we present the spectral variational multiscale enrichment approach that allows the analysis of a broad range of material microstructures for phononic crystals and acoustic metamaterials. The spectral coarse-scale representation is proposed to capture the salient transient wave phenomena, such as wave dispersion and band gaps that occur in the short wavelength regime. A material phase based model order reduction strategy is devised at the fine-scale. By using the reduced basis for the fine-scale problem, significant numerical efficiency is achieved. Transient elastic wave propagation in two-dimensional phononic crystals and acoustic metamaterials are investigated and the proposed multiscale approach is verified against direct numerical simulations.

Coulomb stress analysis for several filling and operational scenarios at the Grand Ethiopian Renaissance Dam impoundment

Increased demand for power generation coupled with changing seasonal water uncertainty has caused a worldwide increase in the construction of large hydrologic engineering structures. That said, the soon-to-be-completed Grand Ethiopian Renaissance Dam (GERD) will impound the Blue Nile River in Western Ethiopia and its reservoir will encompass ~ 1763 km2 and store ~ 67 Gt (km3) of surface water. The impoundment will undergo maximum seasonal load changes of ~ 28 to ~ 36 Gt during projected seasonal hydroelectric operations. The GERD impoundment will cause significant subsurficial stresses, and could possibly trigger seismicity in the region. This study examines Coulomb stress and hydrologic load centroid movements for several GERD impoundment and operational scenarios. The maximum subsurficial Coulomb stress applied on optimally oriented fault planes from the full impoundment is ~ 186 kPa and over 30% of our model domain incurs Coulomb stresses ≥ 10 kPa, regardless of the impoundment period length. The main driver behind Coulomb stress and load centroid motion during impoundment is the annual, accumulated daily reservoir storage change. The maximum Coulomb stresses from the highest amplitude season of five long-term operational scenarios are around 36, 33, 29, 41, and 24% of the total maximum stresses from the entire GERD impoundment. Variations in annual Coulomb stresses during modeled GERD operations are attributed to the seasonal load per unit area, and partially to the initial seasonal water level. The spatial patterns and amplitudes of these stress tensors are closely linked to both the size and timing of GERD inflow/outflow rates, and an improved understanding of the magnitude and extent of these stresses provides useful information to water managers to better understand potential reservoir triggered seismic events from several different operational and impoundment strategies.

Supporting Undergraduate STEMM Education: Perspectives from Faculty Mentors and Learning Assistants in Calculus II

In higher education, Learning Assistants (LAs)—a relatively recent evolution grounded in peer mentorship models—are gaining popularity in classrooms as universities strive to meet the needs of undergraduate learners. Unlike Teaching Assistants, LAs are undergraduate students who receive continuous training from faculty mentors in content-area coaching and pedagogical skills. As near-peers, they assist assigned groups of undergraduates (students) during class. Research on LAs suggests that they are significant in mitigating high Drop-Fail-Withdrawal rates of large enrollment undergraduate science, technology, engineering, mathematics, and medical (STEMM) courses. However, there is a dearth of description regarding the learning between LAs and STEMM faculty mentors. This paper reports on perspectives of faculty mentors and their cooperating LAs in regard to their learning relationships during a Calculus II at a research-oriented university during Spring of 2020. Using an exploratory-descriptive qualitative design, faculty (oral responses) and LAs (written responses) reflected on their relationship. Content analysis (coding) resulted in four salient categories (by faculty and LA percentages, respectively) in: Showing Care and Fostering Relationships (47%, 23%); Honing Pedagogical Skills (27%, 36%); Being Prepared for Class and Students (23%, 28%); and Developing Content Knowledge in Calculus (3%, 13%). Benefits of LAs to faculty and ways to commence LA programs at institutions are also discussed.

Multitemporal Analysis of Land Use and Land Cover within an Oil Block in the Ecuadorian Amazon

The Ecuadorian Amazon is considered a biodiverse region, and at the same time contains the largest number of oil blocks and oilfields in the country. Oil exploitation requires the implementation of oil facilities and related infrastructure, such as roads, water, and energy supply, for operation. These large engineering works can alter the dynamics of the Amazonian natural ecosystems. This paper analyzes the land use and land cover (LULC) change and relates spatial patterns within an oil block located in the province of Orellana, Ecuador. The study was processed in two phases, the first corresponding to the collection and classification of LULC classes within the oil block. The second phase concerned the calculation of landscape metrics, with the purpose of quantitatively characterizing each class. This analysis was carried out for the pre-concession, post-concession scenarios of the oil block and the current scenario of the region. The results revealed that the low predominance of forest cover within the study region is not directly associated with the beginning of the Block 47 concession. On the other hand, a significant reduction of the Coca River was evidenced for the 2018 scenario.

Spreading of performance fluctuations on real-world project networks

Understanding the role of individual nodes is a key challenge in the study of spreading processes on networks. In this work we propose a novel metric, the reachability-heterogeneity (RH), to quantify the contribution of each node to the robustness of the network against a spreading process. We then introduce a dataset consisting of four large engineering projects described by their activity networks, including records of the performance of each activity, i.e., whether it was timely delivered or delayed; such data, describing the spreading of performance fluctuations across activities, can be used as a reliable ground truth for the study of spreading phenomena on networks. We test the validity of the RH metric on these project networks, and discover that nodes scoring low in RH tend to consistently perform better. We also compare RH and seven other node metrics, showing that the former is highly interdependent with activity performance. Given the context agnostic nature of RH, our results, based on real-world data, signify the role that network structure plays with respect to overall project performance.

Using head mounted display virtual reality simulations in large engineering classes: Operating vs observing

A barrier to using head mounted display (HMD) virtual reality (VR) in education is access to hardware for large classes. This paper compares students’ learning when engaging with an HMD VR simulation as the operator and as the observer, to evaluate whether benefits of HMD VR can be achieved without requiring all students to operate the equipment. Postgraduate engineering students (N = 117) completed a safety hazard identification exercise in a workshop. The performance of students who operated and observed was compared. Results showed that students performed similarly in the exercise that followed the simulation whether they operated HMD VR (n = 33) or observed (n = 84). The finding suggests that educators may be able to use HMD VR simulations in classes with a large enrolment, by reducing the need for investment and management of a large number of sets of HMD VR equipment.
 Implications for practice or policy:
 
 Engineering educators can use HMD VR simulations to teach students about safety in design.
 Engineering students are able to identify safety hazards in a HMD VR simulation effectively whether they are operating the equipment or observing another student in their group operating the VR equipment.
 One HMD VR set per student group is sufficient.
 HMD VR simulations can be used inclusively, even when some students are unable or unwilling to wear the headset.
 

Development of a tool for the preliminary design of large engine prechambers using machine learning approaches

Abstract The design of internal combustion engine prechambers requires the consideration of a wide range of parameters. Especially in large gas engines, the design of the prechamber has a significant influence on the combustion process and thus on engine performance and emissions. Since the testing of design parameter combinations on engine test beds is both time-consuming and expensive and even complex 3D computational fluid dynamics (CFD) simulations of the high number of combinations are computationally expensive, this paper presents a novel approach, condensing complex CFD simulations of the prechamber and the engine combustion chamber into simple simulations. The short computational time of the simplified simulations permits the analysis of a wide range of prechamber parameter variations. Based on the simulation results, a model to predict the prechamber behavior is developed using machine learning methods. The parameters considered are maximum impulse, pressure difference between the prechamber and main combustion chamber and their associated crank angles, and NOx level. Several approaches are applied and subsequently validated their prediction accuracy is assessed. In the present case, an artificial neural network (ANN) performed best. The model is tested on geometry and equivalence ratio variations of a real large gas engine prechamber. A comparison of the values predicted with the trained ANN are compared to CFD results generated by a baseline simulation setup. The results indicate that the model is able to satisfactorily predict trends for impulse, pressure difference and NOx level. Absolute values of maximum impulse and pressure difference crank angle can be predicted with a deviation less than 10%.

Portland cement electrolyte for structural supercapacitor in building application

Inorganic cementitious materials based supercapacitors have been attracting interest due to their critical role in large scale civil engineering applications. Normally, inorganic cementitious materials act as structural phases, which are soaked in KOH aqueous solution to assemble into structural electrolytes. Nine 2 wt% alkali metal salts were mixed with Portland cement in advance rather than immersed in their aqueous solution to fabricate structural electrolytes for the first time in this work. The microstructure and multifunctional performances of Portland cement electrolytes were studied as a function of phase composition for various formulated high performance cement systems. The 2 wt% Na2SO4-Portland cement sample showed the best multifunctional properties with an ionic conductivity of 0.062 S cm−1 and a compressive strength of 32.67 MPa. The resulting Portland cement electrolytes were also assembled with rGO foam electrodes into structural supercapacitors, which exhibited a highest areal capacitance of 35.18 mF cm−2. The reported structural supercapacitors in the form of cement-matrix composites are important for large scale civil engineering application.

Influence of nozzle geometry on spray and combustion characteristics related to large two-stroke engine fuel injection systems

As emission regulations for large two-stroke marine Diesel engines increase as well, the manufacturers face similar problems as small-sized engine builders. The fuel injection, spray formation and subsequent combustion process remain among the main drivers for emissions of direct-injection, compression-ignition internal combustion engines. Since the fuel injection nozzle design of large two-stroke marine Diesel engines differs significantly, not only in size but especially regarding their non-symmetricity and eccentrical orifice arrangement, compared with four-stroke engines, the bulk of research available related to this topic is very limited.To further deepen the understanding of how in-nozzle cavitation flow during the fuel injection process affects the combustion behaviour in large two-stroke marine Diesel engines, transparent nozzle geometries have been used to link the cavitation phenomena with spray and combustion characteristics. A total of six single-orifice nozzles based on the original five-orifice nozzle design of large two-stroke marine Diesel fuel injectors, with and without hydro-erosive grinding, have been experimentally investigated under realistic engine conditions using highspeed optical measurement techniques and a unique constant-volume spray chamber that geometrically represents a combustion chamber of a large two-stroke marine Diesel engine at top dead centre.The spray morphology and combustion results reveal significant differences between the non- and hydro-erosive ground nozzle geometries. While the standard and angled nozzle versions remain similar, the eccentrical nozzle with its distinctive in-nozzle swirl cavitation pattern behaves differently, leading to a very reliable start of ignition behaviour and extreme wide spray angle.

Cluster mechanism of industrial development based on the possibility of saving on the growth of production scales

In recent years, the economic development trend in Russia and other countries has been based on the cluster approach. Increasing competitiveness through the use of the cluster mechanism is an effective means of developing industrial production, where the main goal of any enterprise is to obtain maximum profit. For a good and successful confrontation in the conditions of market competition, Russia needs to create large industrial corporations - centers, conduct integration processes and form large regional clusters. The formation of large regional engineering clusters within the subjects of the Russian Federation will ensure the inflow of investment from outside, and will create conditions for competitive advantage for large, small and medium-sized businesses in general. Therefore, we can conclude that the development of the tasks presented in the research, which identified the main ways of cluster development based on the creation of a regional industrial engineering cluster, is relevant, and has novelty and practical significance.

Assessing the Time-Frequency Co-Movements among the Five Largest Engineering Consulting Companies: A Wavelet-Base Metrics of Contagion and VaR Ratio

Diversification in a portfolio is an important tool for the systematic risk management that is inherent to different asset classes. The composition of a portfolio with domestic and international assets is seen as one of the main alternatives for building a diversified portfolio, as this approach tends to reduce portfolio return exposure depending on country factors. However, in scenarios where industry factors are predominant, international diversification can increase systematic risk in a portfolio centered on a single asset class. This study is a pioneer in using wavelet-based methods to identify intersectoral co-movements, based on a portfolio of shares of the world’s top five consulting engineering companies, providing an innovative way to be applied to this phenomenon. Our evidence indicates that companies share a strong pattern of co-movements among themselves, especially in cycles of 32 to 64 days, suggesting a higher exposure to risk for portfolios with an investment horizon in long-term cycles.