Abu Sadat Md. Sayem, Karu P. Esselle, Dushmantha N. Thalakotuna
et al.
In this article, a chip-fed millimeter-wave high-gain antenna system with in-antenna power combining capability is presented. A low-profile resonant cavity antenna (RCA) array is fed by multiple spherical dielectric resonators (DRs), demonstrating its multi-feed capabilities. Each of the DRs is fed by two microstrip resonators on a planar circuit board. A printed superstrate is used in the proposed RCA as the partially reflecting superstrate (PRS), which makes the antenna profile small. To increase the directivity and gain, a 2 × 2 RCA array is developed. The demonstrated design shows a prominent peak gain of 25.03 dBi, a radiation efficiency of more than 80% and 3.38 GHz 3 db gain-bandwidth while maintaining a low profile. To steer the beam of the demonstrated 2 × 2 RCA array in a wide angular range with a low side-lobe-level, two planar all-dielectric passive beam steering metasurfaces have been designed and optimized. A detailed analysis of the optimization procedure is presented in this article. This numerical investigation is vitally important for realizing beam steering metasurfaces with suppressed side-lobe-level, wide bandwidth, excellent efficiency and less complexity.
To address the measurement instability of reflective ultrasonic anemometers in complex wind fields, this study systematically investigates the mechanisms by which shadow effects caused by transducers and reflector support pillars affect measurement accuracy under varying wind speeds and directions. By integrating particle image velocimetry (PIV) experiments with computational fluid dynamics (CFD) simulations, 1:1 and 1:2 scale models are employed to reveal the flow field characteristics and error mechanisms. The results indicate that at a wind direction of 0°, wall-following vortices and turbulent wakes generated by transducer structures cause systematic wind speed deviations along the measurement paths. At a 45° wind direction, flow disturbances around the support pillars become the dominant source of shadow effects. The 1:1 scale model exhibits insufficient decay of large-scale, low-frequency turbulent energy, resulting in the accumulation of turbulent kinetic energy and significant wind speed errors at 0°. In contrast, the 1:2 scale model enables efficient energy transfer through high-frequency, small-scale vortices, enhances vortex intensity uniformity, and achieves improved spatial homogeneity in cross-wind measurement errors. These findings provide an important theoretical foundation for improving the high-precision measurement performance of reflective ultrasonic anemometers in complex wind environments.
Rolling bearings are indispensable components of many engineering machinery, especially rotating machinery. If rolling bearing faults are not diagnosed promptly, it may cause huge economic losses. Bearing fault diagnosis can avoid catastrophic accidents, ensure the reliability of equipment operation, and reduce maintenance costs. Existing intelligent bearing fault diagnosis methods have fast diagnosis speeds and excellent fault recognition capabilities, which is not feasible for most important mechanical devices because of the difficulty in obtaining fault samples for training. To tackle this problem, a two-stage bearing fault diagnosis method without fault sample training based on fault feature knowledge is proposed. In the first stage, a fault detection vector is constructed based on signal statistical indicators. The Mahalanobis distance of the feature vector between online signals and historical normal signals serves for anomaly detection. In the second stage, based on the bearing fault knowledge, envelope spectrum fault indicators are proposed to form diagnosis vectors. By calculating the similarity between the diagnosis vector and the present fault label, the probability of different fault types will be obtained. Three experimental analyses show that the method is effective in detecting early faults and achieves high fault identification accuracy. The above results advantageously prove that the method can be used for fault diagnosis without fault sample training, and has the possibility of practical application.
The powerful functions of materials in the living world utilize supramolecular systems in which molecules self-assemble through noncovalent connections programmed by their structures. This process is of course also programmed by the nature of the chemical environment in which the structures form introducing the potential to autonomously use external energy inputs partly derived from fuel molecules. Our laboratory has focused over the past three decades on integrating this notion of bioinspired supramolecular engineering into the design of novel materials. We present here three projects on functional supramolecular materials that address important societal needs for our future. The first is inspired by the photosynthetic machinery of green plants, creating materials that harvest light to produce fuels for sustainable energy systems. The second example is that of life-like robotic materials that imitate living creatures and effectively transduce different types of energy into mechanical actuation and locomotion of objects for future technologies. The third topic is supramolecular biomaterials that mimic extracellular matrices and provide unprecedented bioactivity to regenerate tissues to achieve longer “healthspans” for humans. In this example, we discuss a recent breakthrough in the structural design of supramolecular motion, which surprisingly led to biomaterials with the potential to reverse paralysis by repairing the brain and the spinal cord.
To improve the wear resistance of the materials used for blades in engineering machinery, this study focused on the microstructural characteristics, mechanical properties, and wear behavior of HB500 grade wear-resistant steel developed using an optimized heat treatment system. To improve the temperature uniformity of the heat treatment furnace, the method of cyclic heating was used to heat the components. Carefully designing the quenching equipment, such as using a cross-shaped press, was employed to enhance the quenching effect and reduce the deformation of the steel plates. The crystal orientation analysis revealed a uniform and fine-grained microstructure, primarily characterized by plate-type tempered martensite, which indicated a good hardenability. The microstructure observations showed that the width of martensite is approximately 200 nm, with a significant presence of dislocations and carbides. Tensile tests and multi-temperature gradient impact tests indicated superior mechanical properties compared to similar grade wear-resistant steels, including a Rockwell hardness of 53, tensile strength of 1610 MPa, yield strength of 1404 MPa, and total elongation around 12.7%. The results of friction and wear experiments indicate that the wear rate decreases as the load increases from 100 N to 300 N, demonstrating an excellent wear resistance under a large load. Observations of the worn surfaces indicated that the wear mainly involved adhesive wear, fatigue wear, and oxidative wear. The properties’ improvements were attributed to microstructure refinement and precipitation strengthening. This study indicates that designing a heat treatment system to control temperature uniformity and stability is feasible.
Simulation of realistic classical mechanical systems is of great importance to many areas of engineering such as robotics, dynamics of rotating machinery and control theory. In this work, we develop quantum algorithms to estimate quantities of interest such as the kinetic energy in a given classical mechanical system in the presence of friction or damping as well as forcing or source terms, which makes the algorithm of practical interest. We show that for such systems, the quantum algorithm scales polynomially with the logarithm of the dimension of the system. We cast this problem in terms of Hamilton's equations of motion (equivalent to the first variation of the Lagrangian) and solve them using quantum algorithms for differential equations. We then consider the hardness of estimating the kinetic energy of a damped coupled oscillator system. We show that estimating the kinetic energy at a given time of this system to within additive precision is BQP hard when the strength of the damping term is bounded by an inverse polynomial in the number of qubits. We then consider the problem of designing optimal control of classical systems, which can be cast as the second variation of the Lagrangian. In this direction, we first consider the Riccati equation, which is a nonlinear differential equation ubiquitous in control theory. We give an efficient quantum algorithm to solve the Riccati differential equation well into the nonlinear regime. To our knowledge, this is the first example of any nonlinear differential equation that can be solved when the strength of the nonlinearity is asymptotically greater than the amount of dissipation. We then show how to use this algorithm to solve the linear quadratic regulator problem, which is an example of the Hamilton-Jacobi-Bellman equation.
Friction in marine engineering machinery produces abrasive particles containing valuable information. By employing oil detection technology, we can analyze these particles to monitor and diagnose mechanical system faults. This paper introduces an inductive oil detection sensor and wireless signal transmission circuit. The sensor utilizes two opposing solenoid coils of the same specifications, with the detection coil connected to a chip capacitor to form an LC resonant unit. The designed wireless transmission circuit wirelessly transmits a sensing signal from a detection coil to a receiving coil to detect metal particles in oil. This paper deduces the sensor’s inductance principle and simulates the magnetic field distribution using finite element simulation software. Through experiments, the optimal excitation frequency, coil spacing, and oil sample flow path location were determined. The sensor successfully detected 55 μm iron particles and 138 μm copper particles in a 1 mm microfluidic channel. With its simple structure, distinct signal characteristics, and high sensitivity, the sensor is suitable for detecting metal abrasive particles in hydraulic oil, providing a new approach for wireless transmission in oil detection sensors.
The contact stiffness of the mechanical joint usually becomes the weakest part of the stiffness for the whole machinery equipment, which is one of the important parameters affecting the dynamic characteristics of the engineering machinery. Based on the three-dimensional Weierstrass–Mandelbrot (WM) function, the novel normal contact stiffness model of the joint with the bi-fractal surface is proposed, which comprehensively considers the effects of elastoplastic deformation of asperity and friction factor. The effect of various parameters (fractal dimension, scaling parameter, material parameter, friction factor) on the normal contact stiffness of the joint is analyzed by numerical simulation. The normal contact stiffness of the joint increases with an increase in the fractal dimension, normal load, and material properties and decreases with an increase in the scaling parameter. Meanwhile, the fractal parameters of the equivalent rough surface of the joint are calculated by the structural function method. The experimental results show that when the load is between 14 and 38 N∙m, the error of the model is within 20%. The normal contact stiffness model of the bi-fractal surface joint can provide a theoretical basis for the analysis of the dynamic characteristics of the whole machine at the design stage.
Heavy-duty machinery demands materials with strong wear resistance and good frictional properties, which conventional materials often lack. The knowledge of PM alloys’ friction and wear characteristics versus standard steel materials is limited. ATOMET 4601, a high-strength prealloyed powder with excellent compressibility, allows for parts with densities over 6.8 g/cm³. Carbon (0, 0.5, 1.0 wt.%) was added to enhance performance. These alloys, compacted to 75% of theoretical density and sintered at 1100 ± 10°C, were tested for wear and friction against EN31 steel. Results showed carbon improved tribological performance, with ATOMET 4601 + 1.0%C exhibiting the best wear resistance. Regression models and interaction plots indicated significant effects of load and speed on wear rate and coefficient of friction. Microstructural analysis revealed carbides and oxides in the ferrite matrix, with adhesive, abrasive, and oxidative wear as primary mechanisms.
Photoacoustic imaging has emerged as a promising modality for medical imaging since its introduction. Photoacoustic microscopy (PAM), which is based on the photoacoustic effect, combines the advantages of both optical and acoustic imaging modalities. PAM facilitates high-sensitivity, high-resolution, non-contact, and non-invasive imaging by employing optical absorption as its primary contrast mechanism. The ability of PAM to specifically image parameters such as blood oxygenation and melanin content makes it a valuable addition to the suite of modern biomedical imaging techniques. This review aims to provide a comprehensive overview of the diverse technical approaches and methods employed by researchers to enhance the resolution of photoacoustic microscopy. Firstly, the fundamental principles of the photoacoustic effect and photoacoustic imaging will be presented. Subsequently, resolution enhancement methods for both acoustic-resolution photoacoustic microscopy (AR-PAM) and optical-resolution photoacoustic microscopy (OR-PAM) will be discussed independently. Finally, the aforementioned resolution enhancement methods for photoacoustic microscopy will be critically evaluated, and the current challenges and future prospects of this technology will be summarized.
The workforce scheduling problem for cell production lines has been recognized as one of the significant issues in manufacturing systems. In most of previous studies, complex workers’ operations in a cell such as traveling times of multi-skilled operators in another cell to their workplaces, have not been considered in the workforce optimization model. In this paper, we consider the simultaneous optimization of the product input sequence and workforce assignment scheduling problem for multi-stage multi-item cell production lines. The problem is formulated as a resource-constrained project scheduling problem (RCPSP). We propose an RCPSP formulation of the scheduling problem for multi-product cell production lines where the traveling time of operators and products are considered. The exact solution of the RCPSP formulation is derived by using a general-purpose solver, Gurobi. The validity of the RCPSP model is verified by comparing it with a genetic algorithm (GA) using a commercial simulation software (Siemens Plant Simulation). Experimental results show that the derived exact solution of RCPSP is better than that of the solutions derived by the GA algorithm in the Siemens Plant Simulation.
Engineering machinery, tools, and implements, Mechanical engineering and machinery
Zhuldyz Tashenova, E. Nurlybaeva, Zhanat Abdugulova
et al.
—The formulation of the proposed methods and algorithms facilitates a comprehensive examination of intricate non-stationary thermo-mechanical processes in rods with varying cross-sectional geometries. Furthermore, it advances the theoretical framework for analyzing the thermo-mechanical properties of rod structures utilized in the machinery industry of the Republic of Kazakhstan. The creation of these intellectual products aids in the progression of this sector and fortifies the nation's sovereignty. This article delineates methods and algorithms for investigating non-stationary thermo-mechanical processes in rods with diverse cross-sectional shapes that influence global manufacturing technologies. The scientific and practical importance of this work lies in the application potential of the developed approach for examining non-stationary thermo-mechanical characteristics of rod-like elements in various installations. The findings also enhance the scientific research direction in mechanical engineering. In conclusion, the article outlines future technological advancements, summarizes the research on non-stationary thermo-mechanical processes in rods with different cross-sectional geometries, and highlights significant economic benefits by facilitating the selection of reliable rods for specified operating conditions. This ensures the continuous and dependable operation of machinery used in mechanical engineering.
Exposure to load and offshore environment degrades the load-bearing capacity of tubular joints, necessitating reinforcement of these joints. Reinforcement is sometimes required for lifespan enhancement or qualification based on new requirements. Available reinforcement techniques include welded rings inside/outside the chord, doubler/collar plate at the brace-chord interface, grout filling, and clamp installation on the joints with/without cement. While these techniques increase the load-bearing capacity of damaged tubular joints, various practical limitations exist. Clamping may require heavy machinery, whereas welding stiffeners involves hot work and may not be permitted sometimes. Fiber-reinforced polymers (FRPs) have immense potential for reinforcing steel structures and are a viable alternative for rehabilitating tubular joints due to their exceptional mechanical and physical characteristics, offering competitive advantages over other methods. FRP reinforcement is becoming more feasible and economical for underwater joints. FRP reinforcement can be either precured, pre-impregnated, or wet layup. Aside from the significance of joint rehabilitation, a document covering the well-known options was lacking. This paper summarizes the advantages and limitations of these reinforcement methods, particularly FRP reinforcement. Possible research directions in FRP reinforcement of tubular joints are also discussed.