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High-performance wrought aluminum alloys, particularly AA6061, are pivotal in industries like automotive and aerospace due to their exceptional strength and good response to heat treatments. Investment casting offers precision manufacturing for these alloys, because casting AA6061 poses challenges like hot cracking and severe shrinkage during solidification. This study aims to address these issues, enabling crack-free investment casting of AA6061, thereby unlocking the full potential of investment casting for high-performance aluminum alloy components.

Nanotechnology is used to enhance the investment casting process, incorporating a small volume fraction of nanoparticles into the alloy melt. The focus is on widely used aluminum alloy 6061, utilizing rapid investment casting (RIC) for both pure AA6061 and nanotechnology-enhanced AA6061. Microstructural characterization involved X-ray diffraction, optical microscopy, scanning electron microscopy, differential scanning calorimetry and energy dispersive X-ray spectroscopy. Mechanical properties were evaluated through microhardness and tensile testing.

The study reveals the success of nanotechnology-enabled investment casting in traditionally challenging wrought aluminum alloys like AA6061. Achieving crack-free casting, enhanced grain morphology and superior mechanical properties, because the nanoparticles control grain sizes and phase growth, overcoming traditional challenges associated with low cooling rates. This breakthrough underscores nanotechnology's transformative impact on the mechanical integrity and casting quality of high-performance aluminum alloys.

This research contributes originality and value by successfully addressing the struggles in investment casting AA6061. The novel nano-treating approach overcomes solidification defects, showcasing the potential of integrating nanotechnology into rapid investment casting. By mitigating challenges in casting high-performance aluminum alloys, this study paves the way for advancements in manufacturing crack-free, high-quality aluminum alloy components, emphasizing nanotechnology's transformative role in precision casting.

Additive manufacturing (AM) can achieve significant weight savings with only minor compromises in strength if high-performance wrought aluminum alloys are used as feedstock. Despite the advantages in strength that aluminum alloys (AA) 6061 offer, they cannot be manufactured via printing because of hot cracking and other solidification problems. The purpose of this study is to achieve high-quality printing of AA6061 with nanotreated wires.

Nanotreating was used to modify the AA6061 alloy composition by adding a small fraction of nanoparticles to enhance the alloy’s manufacturability and resultant properties. Wire arc additive manufacturing (WAAM) was used to print the nanotreated AA6061 wire feedstock. The microstructure of the printed AA6061 was characterized by X-ray crystallography, optical microscopy, scanning electron microscopy and energy dispersive spectroscopy mapping. The microhardness profile, tensile behavior and fracture surface were analyzed.

This work successfully used WAAM to print nanotreated AA 6061 components. The resulting AA6061 parts were crack-free, with exceptional grain morphology and superior mechanical properties. Owing to the excellent size control capabilities of nanoparticles, a homogeneous distribution of small grains was maintained in all deposited layers, even during repeated thermal cycles.

Previous studies have not successfully printed AA6061 using WAAM. Conventional WAAM products exhibit anisotropic mechanical properties. The nanotreated AA6061 was successfully printed to achieve homogeneous microhardness and isotropic tensile properties. The promising results of this study reflect the great potential of nanotech metallurgy as applied to the WAAM process.

It is often important to acquire information such as temperature and strain values from metallic tools and structures in situ. With embedded sensors, structures are capable of monitoring parameters at critical locations not accessible to ordinary sensors. To embed sensors in the functional structures, especially metallic structures, layered manufacturing is a methodology capable of rapidly and economically integrating sensors during the production of tooling or structural components. Embedding techniques for both fiber‐optic sensors and thin‐film sensors have been developed.

The limited strength of polylactic acid (PLA) hinders its extensive engineering applications. This paper aims to enhance its strength and realize diverse applications.

Here, the continuous fiber reinforced PLA composites are fabricated by a customized fused filament fabrication three-dimensional printer. Uniaxial tensile and three-point flexural tests have been conducted to analyze the reinforcement effect of the proposed composites. To unveil the adhering mechanism of optic fiber (OF) and PLA, post failure analysis including the micro imaging and morphology have been performed. The underlying mechanism is that the axial tensile strength of the OF and the interfacial adhesion between PLA and OF compete to enhance the mechanical properties of the composite.

It is found that 10%–20% enhancement of strength, ductility and toughness due to the incorporation of the continuous OF.

The continuous OFs are put into PLA first time to improve the strength. The fabrication method and process reported here are potentially applied in such engineering applications as aerospace, defense, auto, medicine, etc.

Deployment of deep neural networks on embedded devices is becoming increasingly popular because it can reduce latency and energy consumption for data communication. This paper aims to give out a method for deployment the deep neural networks on a quad-rotor aircraft for further expanding its application scope.

In this paper, a design scheme is proposed to implement the flight mission of the quad-rotor aircraft based on multi-sensor fusion. It integrates attitude acquisition module, global positioning system position acquisition module, optical flow sensor, ultrasonic sensor and Bluetooth communication module, etc. A 32-bit microcontroller is adopted as the main controller for the quad-rotor aircraft. To make the quad-rotor aircraft be more intelligent, the study also proposes a method to deploy the pre-trained deep neural networks model on the microcontroller based on the software packages of the RT-Thread internet of things operating system.

This design provides a simple and efficient design scheme to further integrate artificial intelligence (AI) algorithm for the control system design of quad-rotor aircraft.

This method provides an application example and a design reference for the implementation of AI algorithms on unmanned aerial vehicle or terminal robots.

This study aims to design an optimized algorithm for low-cost pedestrian navigation system (PNS) to correct the heading drift and altitude error, thus achieving high-precise pedestrian location in both two-dimensional (2-D) and three-dimensional (3-D) space.

A novel heading correction algorithm based on smoothing filter at the terminal of zero velocity interval (ZVI) is proposed in the paper. This algorithm adopts the magnetic sensor to calculate all the heading angles in the ZVI and then applies a smoothing filter to obtain the optimal heading angle. Furthermore, heading correction is executed at the terminal moment of ZVI. Meanwhile, an altitude correction algorithm based on step height constraint is proposed to suppress the altitude channel divergence of strapdown inertial navigation system by using the step height as the measurement of the Kalman filter.

The verification experiments were carried out in 2-D and 3-D space to evaluate the performance of the proposed pedestrian navigation algorithm. The results show that the heading drift and altitude error were well corrected. Meanwhile, the path calculated by the novel algorithm has a higher match degree with the reference trajectory, and the positioning errors of the 2-D and 3-D trajectories are both less than 0.5 per cent.

Besides zero velocity update, another two problems, namely, heading drift and altitude error in the PNS, are solved, which ensures the high positioning precision of pedestrian in indoor and outdoor environments.

This paper propose an algorithm for the multiple silicon steel coils multiperiod two-dimensional lengthwise cutting stock problem (m2DLCSP), so as to minimize the total cost of materials and production.

The authors propose a sequential leftovers utilization correction (SLUC) algorithm for the m2DLCSP. The algorithm primarily considers three optimization strategies. First, it considers usable leftovers to simplify the cutting process and improve material utilization. The total quantity and types of leftovers should be limited in order to avoid leftover overstock. Second, it uses a splice method of items to improve the generated cutting plan. Third, it takes into account operational restrictions in the cutting operations. Operational restrictions include imposing maximum and minimum lengths on the cutting patterns, and the limitation of cutting knives at the slitting machines.

Several sets of benchmark with real-world and randomly generated instances are provided to evaluate the algorithm. Compared with literature algorithm and current procedure applied in enterprises, the computational results indicate that proposed algorithm can effectively reduce the total cost, and the computation time is reasonable for practical use.

This algorithm can effectively reduce the total cost.

The proposed method can effectively applied to solve the m2DLCSP and improve the economic efficiency of enterprises.

In practical engineering, there are various sequences. The purpose of this paper is to improve and put forward a new model.

Based on the generalized accumulated generating operation, the paper improved the GM(1,1) cosine model and proposed the GAGM(1,1) cosine model.

It is found that the GAGM(1,1) cosine model can satisfy many kinds of periodic sequences and the precision of GAGM(1,1) cosine model is higher than the GM(1,1) model.

The paper shows that the GAGM(1,1) cosine model has important theoretic and practical significance.

To observe the relations between three important factors resulting in estuarial Hypoxia phenomena of Yangtze River – wind, river flow, and stratification. The purpose of the paper is to analyze the possible reasons why hypoxia occurs in late spring and disappears in October.

To overcome the difficulty in examining the role of physical and biological factors affecting hypoxia based on measurement alone, finite-volume community ocean model (FVCOM) was introduced into the investigation. Observed freshwater flux data from Yangtze River, monthly averaged wind speed data, and other observed data were input into the model; the accuracy of which was validated with various kinds of data. The authors used the trajectories of Lagrangian particles from Yangtze River to study the regions of strong riverine influence under different wind forcing conditions and compared the simulation results with former observations.

Trade wind is a significant factor to influence the forming and receding of hypoxia across the Yangtze River.

Using FVCOM to investigate estuary hypoxia is more economical and effective.

Over the past 20 years, China's infrastructure has developed at an extraordinary speed. The current literature mainly focuses on the effects of political incentives on the infrastructure. However, this paper indicates that the structural change of China's land regime is an important clue and that the supernormal development of China's infrastructure is an explicable result for that.

This paper theoretically proves that in a politically centralized and economically decentralized economic entity with a public land-ownership regime, the self-financing mechanism formed by local officials through regulation of the land-grant price is the primary factor that influences the optimal supply volume of infrastructure in a region, in addition to political and economic incentives, and whether the self-financing mechanism can be formed or not depends on the structure of a country's land regime, which can help to explain the difference between the development of infrastructure in China and that in other developing countries from a theoretical angle.

The paper suggests that the mode is facing an important transformation toward land reform and new-type urbanization construction, and the replication and promotion of China's experience in infrastructure construction are of further significance under the Belt and Road Initiative as it provides a method for helping developing countries to eliminate infrastructure bottlenecks.

Through the test of multinational panel data, the paper indicates that the structural change of China's land regime around 1990 had an overall effect on the supernormal development of infrastructure in China. The paper indicates that the “land-based development mode” of China's infrastructure indeed contributed to the supernormal development of infrastructure in China, but there are still some shortcomings in this mode.