Operational Requirements Research Articles

The impact of simulated total surface current velocity observations on operational ocean forecasting and requirements for future satellite missions

The impact of simulated total surface current velocity observations on operational ocean forecasting and requirements for future satellite missions

Air quality perceptual index approach: Development and application with data from two Nigerian cities

Due to the world's population growth, poor air quality (PAQ) has become a major health and environmental issue. Cities, in particular, have had to face the challenge of PAQ as a result of traffic and, in the case of the developing world, the use of diesel generators for domestic and industrial energy supply. As with other societal issues, such as corruption, that have perceptual indices to aid with their assessment, an Air Quality Perception Index (AQPI) could be pivotal in the assessment of air quality (AQ). The use of reference or instrument-measured information has been at the forefront of environmental assessment, but a perception-based index could provide a valuable supplementary approach. This paper discusses the potential for an AQPI based on research that took place on perceptions of air quality by residents in two cities, Abuja and Enugu, in Nigeria. The research was based on a survey of respondents who were asked to score various perceptual indicators of AQ. Utilizing the three most frequently perceived indicators of AQ identified in the survey, dust, smoke and smell/odour, an AQPI is presented and illustrated. The proposed AQPI follows a similar logic to that set out for the Human Development Index, with values that range from 0 to 1, with higher values suggesting better AQ. The paper makes the case for the AQPI as a complement to instrument-measured outcomes especially when the latter are rarely available such as in many cities of the global south due to high cost and operational capacity requirements.

Multi-level and multi-objective structural optimization for hypersonic vehicle design

This research introduces a novel methodology for optimizing the structural design of a full-scale hypersonic aircraft, integrating a multifaceted approach across different levels of modelling detail to enhance a variety of performance metrics. The proposed approach is capable of reduce the vehicle mass, while meeting the necessary operational requirements and maintaining an acceptable computational cost. The methodology, based on a coupled bi-level size optimization and denoted as single-objective bi-level optimization (SOBLO), is applied to the passenger cabin of the STRATOFLY MR3 hypersonic cruiser vehicle. This results in a substantial reduction in the baseline concept design weight, estimated to be more than half on average. The procedure is extended to incorporate a multi-objective optimization approach (MOBLO), which generates a Pareto frontier that provides significant information for selecting the optimal trade-off design, considering manufacturability constraints. The outcomes underscore the efficacy of the proposed methodology and highlight its usefulness in sizing complex aircraft configurations, particularly under the demanding loads imposed by a hypersonic flight regime. This approach has the potential to improve the overall production process and enable designers to attain feasible structural design solutions during early stages of development.

Underwater fluid-driven soft dock for dynamic recovery of AUVs with improved pose tolerance

Recovering autonomous underwater vehicles (AUVs) by a mobile platform is a complex challenge. Traditional docking stations require strict pose deviation from the underwater vehicle. To overcome this issue, we propose a novel solution: an in-situ fluid-driven soft dock. This system comprises three soft robotic manipulators that possess guiding, capturing, and securing functionalities, respectively. We present the design, fabrication, and control methods for each manipulator considering the requirements of underwater docking operations. The theoretically allowable docking pose deviation range during AUV docking is analyzed. Additionally, the required force of soft grippers was evaluated through simulation and equivalent experimental tests. To enable dynamic recovery of AUVs while the soft robotic manipulators remain mobile on the experimental platform, we introduce a hydraulic control method based on attitude and pressure feedback. The test results indicate that the designed soft manipulators can operate and maintain good sealing performance under an external pressure of no less than 11 MPa. Moreover, the soft dock successfully recovered and secured AUVs of two different diameters in 20 dynamic tests, achieving a 90% success rate with a maximum AUV velocity of 1.6 m/s.

Open-source and low-cost miniature microscope for on-site fluorescence detection

The development of a compact and affordable fluorescence microscope can be a formidable challenge for growing needs in on-site testing and detection of fluorescent labeled biological systems, especially for those who specialize in biology rather than in engineering. In response to such a situation, we present an open-source miniature fluorescence microscope using Raspberry Pi. Our fluorescence microscope, with dimensions of 19.2 × 13.6 × 8.2 cm3 (including the display, computer, light-blocking case, and other operational requirements), not only offers cost-effectiveness (costing less than $500) but is also highly customizable to meet specific application needs. The 12.3-megapixel Raspberry Pi HQ Camera captures high-resolution imagery, while the equipped wide-angle lens provides a field of view measuring 21 × 15 mm2. The integrated wireless LAN in the Raspberry Pi, along with software-controllable high-powered fluorescence LEDs, holds potential for a wide range of applications. This open-source fluorescence microscope offers biohybrid sensor developers a versatile tool to streamline unfamiliar mechanical design tasks and open new opportunities for on-site fluorescence detections.

Real-time train timetabling with virtual coupling operations on a Y-type metro line

The spatiotemporal imbalance of passenger flows is a prominent characteristic of urban rail transit systems. To match the provided transportation capacity with passenger distribution, this study considers an integer linear programming model to optimize train operation on a Y-type line, including the train timetable, rolling stock circulation plan and virtual coupling/uncoupling strategy that enables trains to switch between different compositions or configurations during operations. To enhance solution efficiency, certain integer decision variables in the model are relaxed to be continuous, and it is proved that this does not affect the optimal value of the model. To account for the dynamic nature of passenger flows, a “prediction + optimization” method with the rolling optimization framework, which utilizes real-time predicted passenger flow data to enable train operations to be performed and adjusted in response, is proposed. Three variants of the proposed model are embedded to meet the real-time requirements of operations. Numerical experiments verify the effectiveness and applicability of our proposed approach, with real-world data from Shanghai Metro Line 5. The computational results demonstrate that our method performs well under operation scenarios with both normal and abnormal passenger flows. Compared to fixed train composition, virtual coupling can perform much better in both peak and off-peak periods.

Design Ideation and Selection of Under-Piston Door for a Two-stroke Marine Engine Using Hybrid TRIZ-biomimetic and MCDM Methods

Design ideation and selection of a two-stroke marine engine under-piston door employing Theory of Inventive Problem Solving (TRIZ), biomimetics, Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is presented in this paper. The study is motivated by exploring bio-composites as potentially suitable substitutes for conventional steel in engine component manufacture. As bio-composites possess lower mechanical properties compared to steel, the geometrical redesign was deemed necessary for any potential material substitution to take place. New under-piston door designs were ideated through the synergy between TRIZ and biomimetics. Computational models were developed, inspired by the Amazon waterlily, the tortoiseshell and the spider web. Mechanical simulation was performed for maximum stress (von Mises), total deformation and volume. With the simulated results of these designs, AHP and TOPSIS provided the solution’s capabilities to decide the best design overall. The design inspired by the Amazon waterlily proved the best and showed lower stress and deformation values compared to the original by 45.25% and 4.5%, respectively. This research provided conclusive evidence that with refined scrutiny of the TRIZ and biomimetic methods, along with AHP and TOPSIS, potential alternatives to conventional materials that offer environmental friendliness without compromising operational requirements can be realised.

A High-Precision Hand-Eye Coordination Localization Method under Convex Relaxation Optimization.

Traditional switching operations require on-site work, and the high voltage generated by arc discharges can pose a risk of injury to the operator. Therefore, a combination of visual servo and robot control is used to localize the switching operation and construct hand-eye calibration equations. The solution to the hand-eye calibration equations is coupled with the rotation matrix and translation vectors, and it depends on the initial value determination. This article presents a convex relaxation global optimization hand-eye calibration algorithm based on dual quaternions. Firstly, the problem model is simplified using the mathematical tools of dual quaternions, and then the linear matrix inequality convex optimization method is used to obtain a rotation matrix with higher accuracy. Afterwards, the calibration equations of the translation vectors are rewritten, and a new objective function is established to solve the coupling influence between them, maintaining positioning precision at approximately 2.9 mm. Considering the impact of noise on the calibration process, Gaussian noise is added to the solutions of the rotation matrix and translation vector to make the data more closely resemble the real scene in order to evaluate the performance of different hand-eye calibration algorithms. Eventually, an experiment comparing different hand-eye calibration methods proves that the proposed algorithm is better than other hand-eye calibration algorithms in terms of calibration accuracy, robustness to noise, and stability, satisfying the accuracy requirements of switching operations.

The Commander’s Place on the Battlefield

News of Russian generals getting killed on the battlefields raises the question of whether a commander should lead an operation remotely, taking advantage of improved technical capabilities, or whether his presence close to the battlefield is necessary to meet the needs of his troops. The requirements of multi-domain operations and multi-domain integration call for command posts with enhanced capabilities along human, informational and physical dimensions. Unfortunately, these types of command posts have become very large, easily recognisable and vulnerable to attack. Alexander Kohli argues that commanders should not exclusively remain in remote command posts but should also provide support close to the front through personal contact with subordinate commanders and troops. Therefore, they must be able to rely on a command post concept encompassing several smaller forward and alternate command posts operating inconspicuously, yet capable of using a comprehensive command and control system. ◼

Analysis and optimization of repetitive positioning precision for kinematic couplings of opto-mechanical components considering uncertainty

Kinematic coupling, as an efficient form of connection, is frequently employed for the repeated assembly and accurate positioning of replaceable opto-mechanical assemblies within high-power solid-state laser systems. During the kinematic coupling process, uncertainties in the mechanical behavior within the contact region often hinder the attainment of consistent positioning precision, potentially leading to an inability to meet operational requirements. This study aims to enhance the repetitive positioning precision of kinematic couplings. A predictive model for repetitive positioning precision is established, accounting for uncertainties in contact region forces. Based on this model, an optimization design of kinematic couplings is conducted to mitigate these challenges. Initially, accounting for uncertainties in mechanical parameters within the contact region, we formulate a static analysis computational model to elucidate the probabilistic distribution of these parameters. Subsequently, employing Hertz contact theory and Holm-Archard wear theory, we quantify the elastic deformation and equivalent wear for each contact region through the calculation of normal pressures. Building upon this foundation, we establish a predictive model for repetitive positioning precision. Finally, optimization design is carried out on the friction coefficient of contact surfaces and the structural dimensions of positioning elements. The proposed optimization design is validated through experimental verification. The findings demonstrate that optimization of structural dimensions and contact surface friction coefficients resulted in enhanced repetitive positioning precision of 35.9 %, effectively ameliorating the assembly quality. This study contributes a quantifiable analytical approach to the prediction and optimization design of repetitive positioning precision in kinematic couplings.

Building Three-dimensional Virtual Historic Fashion Museum Exhibitions: From the Perspective of Technology Affordances

Museums are currently undertaking the task of digital transformation. Transformational technology generates revitalization of the curatorship, cultural heritage presentation, management model, and traditional roles of museums. The creation of three-dimensional (3D) virtual museum exhibitions is important to fulfill the revolutionary operational requirements and projections of recent museums through digital transformation. The objectives of this project were to (1) create realistic 3D virtual museum exhibitions accessible from the web, focusing on historic fashions, and (2) provide an analysis of the process and resources for creating 3D virtual museum exhibitions featuring object-focused exhibits. As a theoretical background of this project, the theory of technology affordances and the affordance actualization process were applied in the creation of 3D virtual museum exhibitions. The results of this project provide cultural heritage museums and institutions with useful precedents for the development of 3D virtual historic fashion museum exhibitions.

A No-Code Automated Machine Learning Platform for the Energy Sector

The energy sector is increasingly leveraging machine learning (ML) to enhance efficiency, sustainability, and decision-making processes. However, the complexity of ML model development and deployment poses significant challenges, particularly in adapting to diverse data environments and operational requirements. This paper presents the development of a No-Code Automated ML (Auto-ML) platform specifically tailored for the energy industry. We introduce a framework that automates critical steps in the ML pipeline, including data preprocessing, feature engineering, model selection, and hyperparameter tuning, while integrating domain-specific knowledge to handle unique industry challenges such as fluctuating energy demands and regulatory compliance. The platform employs a modular architecture that allows for customization and scalability, facilitating its adaptation across various energy sub-sectors, including renewable energy, oil and gas, and power distribution. The results underline the platform's potential to democratize advanced analytical capabilities within the energy industry, making sophisticated data-driven insights accessible even to non-expert users. This paper contributes to the field by detailing the architectural considerations, implementation challenges, and practical impacts of Auto-ML in a sector critical to global infrastructure and economic stability.

Microstructure and durability of rapid repair mortar with self-emulsifying waterborne epoxy polymer

Due to the low hydration rate of ordinary Portland cement (OPC), it cannot meet the requirements of rapid repair, especially in negative temperature environments. Simultaneously, facing the harsh marine environment, repair materials urgently need high durability. In this paper, a self-emulsifying waterborne epoxy polymer (WEP) suitable for cement systems was combined with sulfoaluminate cement (SAC) to prepare repair materials. The effect of the WEP on the development of microstructure, auto-drying shrinkage and durability was investigated by nuclear magnetic resonance, XRD and SEM methods. Results showed that a continuous interpenetration polymer network (IPN) was intricately woven within the multiphase composites, using the macromolecular network structure formed by —OH groups in WEP and Ca2+ and Al3+ in cement as a bridge. The resistance to chloride migration and water absorption exhibited an increase followed by a decrease. In particular, the resistance to chloride migration was improved by 45 %. Similar trends were observed for the carbonation resistance. Due to the lower porosity and capillary pressure caused by IPN, leading to a decrease in auto-drying shrinkage. Nevertheless, the larger percentage of capillary pores in a mortar with a P/C of 15 % increased the auto-drying shrinkage. The WEP decreased the availability of pores of critical diameter (14 nm) of mortar exposed to water freezing, leading to an increase in the freeze-thaw resistance. The change in P/C hardly affected the resistance to sulfate attack. Under −10°C, at 2 hours, the compressive strength of CSA-based mortar satisfied the load requirements for vehicular operations. This research provides theoretical and practical implications for the repair work of large-scale projects serving in harsh environments.

Measurement of space charge density distributions and dielectric resonance enhancement of beam deflection properties of KTN crystal

In recent years, potassium tantalum niobate (KTN) electro-optical deflection devices have gained considerable attention because of their notable advantages, such as large deflection angles, low operational voltage requirements, and compact dimensions. This study uses the phase-shifted interferometric optical path to characterize the influence of direct current (DC) voltage on charge density. An interferogram is acquired using the four-step phase-shifting technique, enabling the calculation of phase delays and deducing the variation in charge density. Experimental results demonstrate that the charge density near the cathode increases with an increase in DC voltage. Subsequently, we utilize the frequency dependence of the dielectric constant of the KTN crystal on the electric field. The dielectric constant can be enhanced when the characteristic frequency of the motion of the polar nanoscale region matches the frequency of the electric field. This field-induced enhancement effect improves the beam deflection performance of the KTN crystal. Application requirements in the field of high-speed random scanning can be realized through the mechanism of the KTN crystal co-acting with DC and alternating current electric fields.

Deep learning adversarial attacks and defenses on license plate recognition system

The breakthroughs in Machine learning and deep neural networks have revolutionized the handling of critical practical challenges, achieving state-of-the-art performance in various computer vision tasks. Notably, the application of deep neural networks in optical character recognition (OCR) has significantly enhanced the performance of OCR systems, making them a pivotal preprocessing component in text analysis pipelines for crucial applications such as license plate recognition (LPR) systems, where the efficiency of OCR is paramount. However, despite the advancements, the integration of deep neural networks in OCR introduces inherent security vulnerabilities, particularly susceptibility to adversarial examples. Adversarial examples in LPR systems are crafted by introducing perturbations to original license plate images, which can effectively compromise the integrity of the license plate recognition process, leading to erroneous license plate number identification. Given that the primary goal of OCR in this context is to accurately recognize license plate numbers, even a single misinterpreted character can significantly impact the overall performance of the LPR system. The vulnerability of LPR systems to adversarial attacks underscores the urgent need to address the security weaknesses inherited from deep neural networks. In response to these challenges, the exploration of alternative defense mechanisms, such as image denoising and in-painting, presents a compelling approach to bolstering the resilience of LPR systems against adversarial attacks. By prioritizing practical implementation and integration of image denoising and inpainting techniques align with the operational requirements of real-world LPR systems. These methods can be seamlessly integrated into existing pipelines, offering pragmatic and accessible means of enhancing security without imposing significant computational overhead. By embracing a multi-faceted approach that combines the strengths of traditional image processing techniques, the research endeavors to develop comprehensive and versatile defense strategies tailored to the specific vulnerabilities and requirements of LPR systems. This holistic approach aims to fortify LPR systems against adversarial threats, thereby fostering increased trust and reliability in the deployment of OCR and LPR technologies across various domains and applications.

Deciphering the Physiognomy of the Military Operational Environment – Factors and Characteristics

Abstract The purpose of this paper is to provide a systematic and detailed analysis of the key components that characterise the military operational environments and that should be considered to improve the effectiveness of the operations process. Also, it focuses on understanding how these salient characteristics might influence capabilities and tactics with particular emphasis on the adaptability of military forces in the face of rapid and unforeseen changes in the operational environment. The research objectives include identifying and assessing the impact of operational environment’s factors, and analysing how military forces adapt to these conditions to maximise their effectiveness. The results highlight the need for continuous adaptability and flexibility of the military forces to respond performantly to the ever-changing operational requirements. Furthermore, the paper demonstrates that military operational effectiveness is closely connected to the ability to anticipate, understand and integrate new technologies, as well as to adjust continuously designated strategies and tactics in the face of the challenges specific to the operational environment.

Design of clean energy based microplastic collection device

Abstract Microplastics are plastic particles with a particle size of less than 5 mm formed after the degradation of plastic by crushing. Microplastics are chemically stable and difficult to degrade, and they are also enriched with chemical poisons, microorganisms, and pathogenic bacteria[1]. Some microplastics migrate with ocean currents in the ocean, affecting the global distribution of pollution and causing great harm to the stability of marine ecosystems and the marine environment. There are a large number of microplastics in the ocean, and the number is increasing[2][3]. In order to realize the microplastic collection function, a microplastic collection device was designed to reduce operational requirements and costs while realizing microplastic salvage. The overall scheme of the system includes the design of subsystems consisting of a solar power generator, a collection mechanism, a filtration device, a buoyancy device, a lighthouse, an anchor device, and so on. According to the actual needs of the microplastic collection, the mechanical structure and dimensions of each subsystem were designed, the 3D modeling of the overall system was completed using SolidWorks, and a physical model of the microplastic collection device was produced for experimental testing.

Stress stiffening effects in flexible Earth observation satellites with spinning appendage

Modern satellites often adopt innovative configurations to meet the escalating requirements of space operations. This study specifically focuses on one such configuration, exemplified by an Earth observation spacecraft equipped with a large rotating payload connected to the main bus through a flexible boom. The rotational motion of the payload is designed to extend the scanned area, resulting in a substantial reduction in the time required to complete a set of measurements, thus enhancing the overall performance. However, this configuration introduces greater complexity both in the analysis of the dynamical behavior and in the design of the control architecture. When dealing with flexible structures subject to rotational motion, as in this scenario, the stiffening effect resulting from inertial loads—particularly the centrifugal action—becomes crucial. In this study, we derive the dynamic equations of the multibody flexible spacecraft using Kane's formulation, which provides a streamlined set of ordinary differential equations by simplifying their derivation. Treating the link as an elastic beam, flexibility is incorporated through a modal decomposition approach that considers nonlinear elastic dynamics, ensuring the inclusion of stress stiffening in the dynamical model. Stress stiffening emerges as a fundamental effect in spinning space structures, where the contribution of the centrifugal force is significant. Incorrect predictions and structural instability for high spinning rates are observed when this effect is neglected. Furthermore, the error associated with overlooking this physical phenomenon is found to be dependent on the spinning rate. We identify kinematical conditions that render this effect negligible in relation to the fundamental deformation frequencies of the space system. Several numerical results are presented and discussed.

Reconfigurable origami-inspired multistable metamorphous structures.

Origami-inspired metamorphous structures can adjust their shapes and mechanical behaviors according to operational requirements. However, they are typically composed of nonrigid origami, where required facet deformation complicates actuation and makes them highly material dependent. In this study, we present a type of origami metamorphous structure composed of modular bistable units, each of which is a rigid origami. The elasticity within the origami creases and switching of mountain and valley crease lines enable it to have bistability. The resultant metamorphous structure has multistability, allowing it to switch among multifarious configurations with programmable profiles. This concept was validated by potential energy analysis and experiments. Using this concept, we developed a robotic limb capable of both lifting and gripping through configuration changes. Furthermore, we used the origami units to construct a metamaterial whose properties could change with the variation of configurations. These examples demonstrate the concept's remarkable versatility and potential for many applications.

Global Copyright Consortium: Empowering Decentralisation with Authority - Backed Blockchain

Abstract: Digital images are transferred with ease through the network. Many users are using the images without the knowledge of the owners. Zero watermarking does not alter the original information contained in vector map data and provides perfect imperceptibility. The use of zero watermarking for data copyright protection has become a significant trend in digital watermarking research. However, zero watermarking encounters tremendous obstacles to its development and application because of its requirement to store copyright information with a third party and its difficulty in confirming copyright ownership. However, traditional digital image generation methods have high operational requirements for designers due to difficulties in collecting data sets and simulating environmental scenes, which results in poor quality, lack of diversity, and long generation speed of generated images, making it difficult to meet the current needs of image generation.