Mathematical Problems in Engineering

This paper investigates the performance of a queueing model with multiple finite queues and a single server. Departures from the queues are synchronised or coupled which means that a service completion leads to a departure in every queue and that service is temporarily interrupted whenever any of the queues is empty. We focus on the numerical analysis of this queueing model in a Markovian setting: the arrivals in the different queues constitute Poisson processes and the service times are exponentially distributed. Taking into account the state space explosion problem associated with multidimensional Markov processes, we calculate the terms in the series expansion in the service rate of the stationary distribution of the Markov chain as well as various performance measures when the system is (i) overloaded and (ii) under intermediate load. Our numerical results reveal that, by calculating the series expansions of performance measures around a few service rates, we get accurate estimates of various performance measures once the load is above 40% to 50%.

Fatigue is among the most critical forms of damage potentially occurring in steel bridges, while accurate assessment or prediction of the fatigue damage status as well as the remaining fatigue life of steel bridges is still a challenging and unsolved issue. There have been numerous investigations on the fatigue damage evaluation and life prediction of steel bridges by use of deterministic or probabilistic methods. The purpose of this review is devoted to presenting a summary on the development history and current status of fatigue condition assessment of steel bridges, containing basic aspects of fatigue, classical fatigue analysis methods, data-driven fatigue life assessment, and reliability-based fatigue condition assessment.

This study deals with natural convection unsteady flow of $\text{CNTs}-{\text{Fe}}_3{\text{O}}_4$ /water hybrid nanofluids due to stretching surface embedded in a porous medium. Both hybrid nanoparticles of $\text{SWCNTs}-{\text{Fe}}_3{\text{O}}_4$ and $\text{MWCNTs}-{\text{Fe}}_3{\text{O}}_4$ are used with water as base fluid. Effects of hybrid nanoparticles volume friction, second-order velocity slip condition, and temperature-dependent viscosity are investigated. The governing problem of flow is solved numerically employing spectral quasilinearization method (SQLM). The results are presented and discussed via embedded parameters using graphs and tables. The results disclose that the thermal conductivity of $\left(\text{CNTs}-{\text{Fe}}_3{\text{O}}_4\right)/{\text{H}}_2\text{O}$ hybrid nanofluids is higher than that of $\text{CNTs}-{\text{H}}_2\text{O}$ nanofluids with higher value of hybrid nanoparticle volume fraction. Also, the results show that momentum boundary layer reduces while the thermal boundary layer gros with higher values of temperature-dependent viscosity and second-order velocity slip parameters. The skin friction coefficient improves, and the local heat transfer rate decreases with higher values of nanoparticle volume fraction, temperature-dependent viscosity, and second-order velocity slip parameters. Furthermore, more skin friction coefficients and lower local heat transfer rate are reported in the $\text{CNTs}-{\text{Fe}}_3{\text{O}}_4/{\text{H}}_2\text{O}$ hybrid nanofluid than in the $\text{CNTs}-{\text{H}}_2\text{O}$ nanofluid. Thus, the obtained results are promising for the application of hybrid nanofluids in the nanotechnology and biomedicine sectors.

Dynamic behavior of axially functionally graded (FG) pipes conveying fluid was investigated numerically by using the generalized integral transform technique (GITT). The transverse vibration equation was integral transformed into a coupled system of second‐order differential equations in the temporal variable. The Mathematica’s built‐in function, NDSolve, was employed to numerically solve the resulting transformed ODE system. Excellent convergence of the proposed eigenfunction expansions was demonstrated for calculating the transverse displacement at various points of axially FG pipes conveying fluid. The proposed approach was verified by comparing the obtained results with the available solutions reported in the literature. Moreover, parametric studies were performed to analyze the effects of Young’s modulus variation, material distribution, and flow velocity on the dynamic behavior of axially FG pipes conveying fluid.

This paper attempts to address the detailed verification of Zhao’s analytical solution including the moment effect with the two- and three-dimensional finite element results. Zhao compared the analytical results with only the 2D FEA results and used the constant bond-length ratio for the biadhesive bondline. In this study, overlap surfaces of the adherends and the adhesives were modelled using surface-to-surface contact elements. Both analytical and numerical analyses were performed using four different biadhesive bondline configurations. The 3D FEA results reveal the existence of complex stress state at the overlap ends. However, the general results show that analytical and numerical results were in a good agreement.

Mục tiêu chính của nghiên cứu này là đánh giá và so sánh hiệu suất của các thuật toán học máy (ML) khác nhau, cụ thể là Mạng Nơron Nhân Tạo (ANN), Máy Học Tăng Cường (ELM) và thuật toán Cây Tăng Cường (Boosted), khi xem xét ảnh hưởng của các tỷ lệ đào tạo đối với kiểm tra trong việc dự đoán độ bền cắt của đất, một trong những tính chất kỹ thuật địa chất quan trọng nhất trong thiết kế và xây dựng công trình. Để thực hiện điều này, một cơ sở dữ liệu gồm 538 mẫu đất thu thập từ dự án nhà máy điện Long Phú 1, Việt Nam, đã được sử dụng để tạo ra các bộ dữ liệu cho quá trình mô hình hóa. Các tỷ lệ khác nhau (tức là 10/90, 20/80, 30/70, 40/60, 50/50, 60/40, 70/30, 80/20, và 90/10) đã được sử dụng để chia bộ dữ liệu thành bộ dữ liệu đào tạo và kiểm tra nhằm đánh giá hiệu suất của các mô hình. Các chỉ số thống kê phổ biến, chẳng hạn như Lỗi Bình Phương Trung Bình (RMSE), Lỗi Tuyệt Đối Trung Bình (MAE) và Hệ Số Tương Quan (R), đã được sử dụng để đánh giá khả năng dự báo của các mô hình dưới các tỷ lệ đào tạo và kiểm tra khác nhau. Ngoài ra, mô phỏng Monte Carlo đã được thực hiện đồng thời để đánh giá hiệu suất của các mô hình đề xuất, có tính đến ảnh hưởng của lấy mẫu ngẫu nhiên. Kết quả cho thấy mặc dù cả ba mô hình ML đều hoạt động tốt, nhưng ANN là mô hình chính xác nhất và ổn định nhất về mặt thống kê sau 1000 lần mô phỏng Monte Carlo (R Trung Bình = 0.9348) so với các mô hình khác như Boosted (R Trung Bình = 0.9192) và ELM (R Trung Bình = 0.8703). Điều tra về hiệu suất của các mô hình cho thấy khả năng dự báo của các mô hình ML bị ảnh hưởng lớn bởi các tỷ lệ đào tạo/kiểm tra, trong đó tỷ lệ 70/30 thể hiện hiệu suất tốt nhất của các mô hình. Một cách ngắn gọn, kết quả được trình bày ở đây thể hiện một cách thức hiệu quả trong việc lựa chọn các tỷ lệ dữ liệu phù hợp và mô hình ML tốt nhất để dự đoán chính xác độ bền cắt của đất, điều này sẽ hữu ích trong các giai đoạn thiết kế và kỹ thuật của các dự án xây dựng.

A timely and accurate understanding of land cover change has great significance in management of area resources. To explore the application of a daily normalized difference vegetation index (NDVI) time series in land cover classification, the present study used HJ‐1 data to derive a daily NDVI time series by pretreatment. Different classifiers were then applied to classify the daily NDVI time series. Finally, the daily NDVI time series were classified based on multiclassifier combination. The results indicate that support vector machine (SVM), spectral angle mapper, and classification and regression tree classifiers can be used to classify daily NDVI time series, with SVM providing the optimal classification. The classifiers of K‐means and Mahalanobis distance are not suited for classification because of their classification accuracy and mechanism, respectively. This study proposes a method of dimensionality reduction based on the statistical features of daily NDVI time series for classification. The method can be applied to land resource information extraction. In addition, an improved multiclassifier combination is proposed. The classification results indicate that the improved multiclassifier combination is superior to different single classifier combinations, particularly regarding subclassifiers with greater differences.

Wheel loaders in the V-type loading cycle are characterized by complicated loading conditions, nonlinear power-train system, and time-variable engine power distribution. Therefore, it is difficult to predict the fuel consumption of wheel loaders in the V-type loading cycle. The static matching methods cannot provide fuel consumption prediction for the loading cycle. In this paper, the prediction method and model of the fuel consumption for wheel loaders in the V-type loading cycle were proposed. Firstly, the hydraulic system data were tested when a wheel loader loaded three different materials in a typical V-type loading cycle. Secondly, the tested data were filtered by the 8th-order Butterworth filter and the dimensionless power deduction equations of hydraulic power system for loading three different materials were obtained by Gaussian and linear fitting based on the filtered data in the loading cycle. Finally, fuel consumption was obtained with the compiling dynamic calculation program as well as input parameters of tested vehicle speed, throttle parameter, and the dimensionless equation. The simulation results agreed well with experiment results. Dynamic calculation program is applicable to calculate loading economy and can provide academic guidance for wheel loader’s design and optimization.

The peristaltic transport of Johnson‐Segalman fluid by means of an infinite train of sinusoidal waves traveling along the walls of a two‐dimensional flexible channel is investigated. The fluid is electrically conducted by a transverse magnetic field. A perturbation solution is obtained for the case in which amplitude ratio is small. Numerical results are reported for various values of the physical parameters of interest.