Environmental Load Research Articles

Dynamic modeling and energy demand analysis of chain heavy load transfer system on marine mobile platform

ABSTRACT The demand for transferring the heavy load on marine mobile platform is steadily increasing, surpassing the capabilities of the current system. This paper introduces a chain heavy load transfer system and develops its dynamic model. This paper studies the sensitivity laws of the system’s energy demand to unknown parameters and proposes an adaptive mutation particle swarm optimization (AMPSO), whose identification accuracy is verified through comparative analysis. Experimental verification confirms the reliability of the system model while studying the influence of environmental loads on the system’s energy demand. The results demonstrate that the chain transfer system meets the requirements of marine mobile platforms, and the system model incorporates the primary influencing factors. Unknown parameters significantly influence the system’s energy demand, and the displacement error after parameter identification using AMPSO is 0.00056 rad, substantially enhancing the accuracy of model calculations. The model calculations of the system closely align with experimental measurements, with a maximum displacement error not exceeding 0.004 rad. Sway exerts a greater influence on the system’s energy demand compared to tilt. When tilt and sway are superimposed, the friction torque between the load and the track results in increased input torque and power for the vertical arrangement of the system, with a maximum torque of 328.6kN·m and maximum power of 400 kW.

Simulation of LNG-Battery hybrid tugboat under the influence of environmental loads and manoeuvre

This paper presents a system modelling approach aimed at designing and simulating real-time conditions, with a specific focus on extreme scenarios to assess the impact on the annual CO2 emissions and the consumption of LNG and batteries in a hybrid tugboat. Environmental variables such as wave period, wave height, current speed, and wind speed are considered. The tugboat system model is validated using manually logged historical operational data from a similar tugboat profile using both AMESIM and MATLAB\Simulink to simulate diverse environmental conditions and estimate annual fuel operational costs and emissions. A comparative analysis of the different system configurations is then conducted between traditional diesel, LNG and several control configurations of LNG-battery hybrid. Results demonstrate a significant reduction of 96.5% in CO2 emissions and a 95.3% decrease in annual fuel operational costs with the adoption of LNG-battery hybrid propulsion with the rule-based control system. The study notes a slight increase in vessel operational time by 10.8% due to higher wave heights and a 0.97% rise in added resistance from increased wind speed. Insignificant differences are observed in variations of wave period and current speed. Additionally, the CII ratings of the different system configurations were then compared and concluded with the LNG-battery hybrid with a rule-based control system being the most environmentally and economically sustainable.

Safety Evaluation of 5G Antenna Mounted on Power Transmission Towers Using a New Mounting Device Under Environmental Loads

Safety Evaluation of 5G Antenna Mounted on Power Transmission Towers Using a New Mounting Device Under Environmental Loads

Environmental prospective of valorizing corn processing effluent to produce ferulic acid grafted chitosan polymer

The food industry requires new production models that include more environmentally friendly waste management practices, considering that the environmental loads of solid waste and wastewater associated with this sector cause damage to the receiving ecosystems. The approach considered in this study focuses on the design and environmental assessment of an enzymatic process for the valorization of ferulic acid present in the effluent of a corn tortilla plant. The ferulic acid can be immobilized on chitosan so that the ferulic acid grafted chitosan can be used as a bioactive film with enhanced antioxidant properties with potential applications in the biotechnology sector.Its real projection approach requires the evaluation of its environmental and economic performance, trying to identify its benefits and potential in the value chain, using the Techno-Economic Analysis (TEA) as a phase for the conceptual design of the process and the Life Cycle Assessment (LCA) methodology for the environmental evaluation. It should be noted that the TEA indicators are promising, since the values of the financial indicators obtained are representative of the economic profitability, which makes the ferulic acid valorization a viable process. In terms of the environmental impact of the process, the buffer dose and the chitosan production process are identified as the main critical points. This double benefit in environmental and economic terms shows that the valorization of ferulic acid for chitosan functionalization is a promising alternative to improve the sustainability performance of corn processing.

Spatial Analysis on Resource Utilization, Environmental Consequences and Sustainability of Rice–Crayfish Rotation System in Jianghan Plain, China

The rice–crayfish rotation system (RCR), originating in the Jianghan Plain, is developing rapidly in various regions of China and has been characterized by unbalanced regional development, which has also led to widespread concerns and discussion on its environmental impacts and sustainability. This study selects representative RCR production areas in the Jianghan Plain, including Jianli, Qianjiang, Shishou, Shayang, Gong’an and Honghu, to analyze resource inputs, resource utilization efficiency, environmental impacts and sustainability by employing the emergy analysis method. Our analysis of Jianli, Honghu, Qianjiang, Gong’an, Shishou and Shayang reports total emergy inputs ranging from 6.46 × 1016 to 8.25 × 1016, with renewable rates between 78.38% and 84.34%. Shishou leads in the unit emergy value (5.58 × 10−1) and the emergy yield ratio (5.30). The sustainability evaluation finds that the environmental loading ratio is from 0.19 to 0.28 and the emergy index for sustainable development varies between 1.27 and 3.00. This analysis indicates that the southern regions have higher inputs and efficiency, with southeastern areas showing lower environmental impact and higher sustainability. We also underscore the impact of non-renewable resources on environmental outcomes and sustainability, suggesting tailored development strategies for the rice–crayfish rotation system’s optimization and sustainable growth.

Passive Shunted Piezoelectric Systems for Vibration Control of Wind Turbine Towers: A Feasibility Study

Many countries have a variety of offshore and onshore wind turbines that face extreme aging challenges. Issues with harmful vibrations that must be minimized are addressed in this paper. A new method of wind turbine tower vibration control using piezoelectricity and shunt circuits is proposed in this paper. The passive vibration control method is shown to improve the tower’s structural performance under various environmental loads, like wind and seismic excitations. To examine the effectiveness of the suggested shunted piezoelectric system, a simple surrogate finite element model of a wind turbine tower is considered, and various investigations at the second eigenfrequency are carried out. An alternative way of modeling the studied structure is considered and the results demonstrate better performance. The advantages of setting up structural damping systems for decreasing tower vibrational loads and boosting their structural stability and resilience against extreme events are highlighted throughout this work.

The Effect of Icon Color Combinations in Information Interfaces on Task Performance under Varying Levels of Cognitive Load

In human–computer interaction interfaces, icons serve as highly symbolic elements that convey information and significantly influence the performance of visual search and other tasks. Thus, the selection of appropriate colors plays a crucial role in the design of human–computer interfaces. This study aimed to investigate the effects of icon color combinations on human visual search task performance across various cognitive load conditions. The experiment was divided into two parts, involving a cognitive load test experiment and an icon search task, wherein the former required participants to select the target icon from 16 de-colored icons, and the latter involved selecting the target icon from 16 color combinations of 8 colors (background colors: black, red, blue, and purple; foreground colors: white, yellow, green, and turquoise). A total of 20 participants (11 females and 9 males, all aged between 18 and 24 years) were recruited for this experiment to perform both tasks sequentially. Through a comprehensive consideration of factors such as the NASA-TLX scale, retrieval time, etc., the experimental results revealed that cognitive load increased with time pressure, resulting in varying optimal color combinations for different cognitive load levels. Additionally, background colors did not affect task response time under different cognitive loads, whereas white foreground color was superior to turquoise foreground color in a medium cognitive load environment. Meanwhile, our results recommend prioritizing white-on-black as the preferred color combination, given that it demonstrated excellent cognitive performance in all three cognitive load environments. Conversely, white-on-blue is not recommended as a color combination for the design of high cognitive load environments. Concerning medium cognitive load environments, yellow-on-red or white-on-purple color combinations were preferred. Finally, in low cognitive load environments, white-on-purple is recommended as the primary color combination. Overall, this study provides a theoretical reference for the future design of interactive interface icons across various contexts.

Vibration analysis of piping connected with shipboard equipment

The piping system connected with the shipboard equipment may be subjected to excessive vibration due to harmonic base excitation produced by hydrodynamic force imposed on the propeller blades interacting with the hull and by other sources. Vibration design aspects for shipboard pipework are often ignored, which may cause catastrophic fatigue failures and, consequently, leakage and spillage in the sea environment. Without dedicated design codes, the integrity of shipboard equipment against this environment loading can be ensured by testing as per test standard MIL-STD-167-1A (2005). However, in many cases, testing is not feasible and economically viable. Hence, this study develops an FE-based vibration analysis methodology based on MIL-STD-167-1A, which can be a valuable tool to optimize the testing requirement without compromising the integrity of these piping systems. The simulated model dynamic properties are validated with experimental modal testing and Harmonic response analysis result confirm that a mitigating solution option can be verified by a FE based vibration analysis to mitigate the vibration problem.

Predictive optimization of DDoS attack mitigation in distributed systems using machine learning

In recent years, cloud computing has been widely used. This paper proposes an innovative approach to solve complex problems in cloud computing resource scheduling and management using machine learning optimization techniques. Through in-depth study of challenges such as low resource utilization and unbalanced load in the cloud environment, this study proposes a comprehensive solution, including optimization methods such as deep learning and genetic algorithm, to improve system performance and efficiency, and thus bring new breakthroughs and progress in the field of cloud computing resource management.Rational allocation of resources plays a crucial role in cloud computing. In the resource allocation of cloud computing, the cloud computing center has limited cloud resources, and users arrive in sequence. Each user requests the cloud computing center to use a certain number of cloud resources at a specific time.

Genotype by environment interaction and stability analysis of three agronomic traits in Kersting's groundnut (Macrotyloma geocarpum) using factor analytic modeling and environmental covariates

AbstractUnderstanding genotype by environment interaction (GEI) represents a challenge in Kersting's groundnut [Macrotyloma geocarpum (Harms) Maréchal and Baudet] breeding for selecting high‐performing and stable lines across environments. Here, we investigated GEI and stability in Kersting's groundnut using factor analytic (FA) based linear mixed models and environmental covariates. A total of 375 accessions were evaluated across 3 years (2017, 2018, and 2019) and two locations (Sékou and Savè) in Benin, generating five environments (E1, E2, E3, E4, and E5). The traits measured included days to 50% flowering (DFF), grain yield (YLD), and 100‐seed weight (HSW). The study generated multi‐environment values for grain yield and its components in Kersting's groundnut. The genetic correlations between pairs of environments ranged from −0.71 to 0.99. The genetic correlations between YLD and HSW indicated positive and moderate to high correlations in all environments. The FA analysis revealed that FA2 structure accounted for 93.9% of the genetic variability in DFF with factor 1 accounting for more than 90% of the environments variations. Two factors explained 87% of the genetic variance in grain yield, and 70% of the environments variability were clustered by factor 1. For HSW, two factors explained 85% of the genetic variance of the environments, and factor 1 accounted for 72.7%. Combining environmental covariates to FA models revealed that precipitation, temperature, and growth cycle duration were highly correlated to the environmental loadings of factor 1. Relative humidity and solar radiation showed moderate to high correlations with factor 2 loadings. Those covariates explained the high GEI among environments clustered by a given factor. Precipitations and temperatures affected the variations in grain yield. Finally, based on latent regression analysis, the accessions AF202, AF221, AF223, AF225, and AF256 were identified as accessions combining best performance for grain yield, early flowering, and 100‐seed weight, showing adaptability across environments and stability to some environments.

Power-law productivity of highly biodiverse agroecosystems supports land recovery and climate resilience

Transformative change in primary food production is urgently needed in the face of climate change and biodiversity loss. Although there are a growing number of studies aimed at global policymaking, actual implementations require on-site analyses of social feasibility anchored by ecological rationale. This article reports the in-depth characterizations of low-input mixed polyculture of highly diverse crops managed on the self-organization of ecosystems, which performed better compared to conventional monoculture methods in Japan and Burkina Faso. Analyses on crop productivity and diversity showed that the primary production of ecosystems followed a power law, and through the underlying mechanisms excelled in (1) promoting diversity and total quantity of products along with the rapid increase of in-field biodiversity, especially useful for the recovery of local regime shift in a semi-arid environment; (2) a fundamental reduction of inputs and environmental load; and (3) ecosystem-based autonomous adaptation of the crop portfolio to climatic variability. The overall benefits imply substantial possibilities of a new typology of sustainable farming for smallholders sensitive to climate change, which could overcome the historical trade-off between productivity and biodiversity based on the human-guided augmentation of ecosystems.

Intelligent control algorithm for dynamic positioning control system

Introduction: The dynamic positioning system resists the environmental forces such as wind, wave and current acting on the ship through the thruster, so that the ship can remain in the position required by the sea level as much as possible, and the operation is very convenient. But its current dynamic positioning ability can not meet people's needs.Methods: A Kalman filter based on untracked optimization was designed for dynamic positioning control system. Then the intelligent control algorithm is designed for the dynamic positioning top-level controller and thrust optimal distribution controller, which occupy an important position in the system, namely the adaptive weight variation particle swarm optimization algorithm and thrust optimal distribution algorithm.Results and Discussion: The average position error of three degrees of freedom after filter processing is 1.53 m. Compared with other mainstream controllers, the mean root error of controllers based on adaptive weight variation particle swarm optimization in environment A and B is 2.295 and 1.8 m, respectively. In environment C, the controller based on thrust optimization allocation algorithm can get the optimal solution when the full rotary thruster reaches the 7 s and the channel thruster reaches the 4 s. The thrust exclusion zone is crossed at 46 s in environment D. In the dynamic positioning capability curve of the system, the experimental hull can balance the different environmental loads at all angles. In summary, the intelligent control algorithm proposed in this paper can effectively improve the positioning ability of the dynamic positioning control system and meet the needs of people for ship navigation today.

Design strategy for resonance avoidance to improve the performance of tension leg platform-type floating offshore wind turbines

The objective of this study is to determine the effect of elasticity of the tower and blades of a large tension leg platform (TLP)-type FOWT on the eigenmodes of the entire system and suggest reference directions to be implemented in the conceptual design stage. Typically, TLP-type FOWTs are connected by a mooring system with strong tension and exhibit an extremely short natural period of motion compared with a semi-submersible platform. Furthermore, the wind turbine tower mounted on the floating platform is flexible in the fore-aft and side-to-side directions, forming a vibrating system in itself; therefore, it is coupled with the motion of the floating platform. In particular, the tower elasticity is known to influence the roll and pitch motions of the platform. In this study, the motion response characteristics of the platform were investigated according to the changes in the tower design parameter (bending stiffness). The influence of blade elasticity was also confirmed, verifying that the physical characteristics of both the tower and blade significantly affect the motion of the TLP. Additionally, the degree of influence based on environmental loads was identified to suggest a design direction for FOWTs while avoiding resonance.

Quantitative analysis of asphalt concrete’s tension-compression asymmetry effects on pavement response through 3D numerical modeling with dual viscoelastic model

Asphalt concrete (AC) exhibits noticeable tension-compression (TC) asymmetry, but it is typically considered isotropic in pavement design. This study aims to quantitatively evaluate the effect of AC’s TC asymmetry on pavement response under loading through numerical modeling. To achieve this objective, a temperature-dependent dual viscoelastic constitutive model was applied to incorporate AC’s TC asymmetry into pavement modeling. Besides, three pavement structure models, including one with thick AC layers, one with thin AC layers, and one with a Portland cement concrete (PCC) base, were developed. The responses of the three pavement structures under traffic and environmental loading conditions were simulated. Modeling results showed that AC’s TC asymmetry can significantly increase the vertical strain in AC, leading to higher stress concentration and larger deformation in AC layers. Unlike the conventional understanding that tensile strain concentrates at the bottom of AC layers, high tensile strains were observed in the top AC layers, especially for the pavement with thick AC layers or a PCC base, which may lead to top-down cracking. High tensile strains were observed on the granular subbase for the pavement with thin AC layers, which may induce bottom-up cracking. Besides, AC’s TC asymmetry also significantly increases the shear strains, especially the horizontal shear strain in AC layers, which may result in debonding and shoving distresses in AC layers. It was also noticed that the pavement response highly depends on its temperature and vehicular speed. A higher temperature or lower vehicular speed leads to more significant AC’s TC asymmetry as well as its effects on asphalt pavement’s response. The outcomes of this study are expected to help enhance the design and maintenance of more durable asphalt pavement.

Numerical Analysis of Dynamic Response in Large Caissons during Wet-towing after Cable Breakage

Variable and complex marine environmental loads combined with wave resistance and the insufficient controllability of large caisson structures pose serious challenges during maritime towing. Cable breakage events are common, and improper behaviors could give rise to a variety of accidents. This work explored the dynamic responses of large caisson structures following towing cable breakage under irregular waves combined with harsh currents. Two types of cable breakage, i.e., main bridle and towing bridle breakage, were taken into account. Four potential wave–current combinations were assumed for each situation according to direction. The obtained results show that drag rope breakage could give rise to lateral shifts in the structure, which can become a serious condition when exposed to angled waves. Additionally, following breakage, significant force fluctuations took place in the remaining intact cables. For main cable breakage, both lateral and backward displacements were observed in the structure, which gradually entered a ‘flowing with the wave’ state. Furthermore, under the two abovementioned cable breakage conditions, the structure air gap consistently exceeded 2.3 m, ignoring the possibility of a wave slamming event.

Impact of earthworms on antibiotic resistance genes removal in ampicillin-contaminated soil through bacterial community alteration.

The emergence of antibiotic resistance genes (ARGs) as contaminants in soil poses a significant threat to public health. Earthworms (Eisenia foetida), which are common inhabitants of soil, have been extensively studied for their influence on ARGs. However, the specific impact of earthworms on penicillin-related ARGs remains unclear. In this study, we investigate the role of earthworms in mitigating ARGs, specifically penicillin-related ARGs, in ampicillin-contaminated soil. Utilizing high-throughput quantitative PCR (HT-qPCR), we quantified a significant reduction in the relative abundance of penicillin-related ARGs in soil treated with earthworms, showing a decrease with a p-value of <0.01. Furthermore, high-throughput 16S rRNA gene sequencing revealed that earthworm intervention markedly alters the microbial community structure, notably enhancing the prevalence of specific bacterial phyla such as Proteobacteria, Firmicutes, Chloroflexi, and Tenericutes. Our findings not only demonstrate the effectiveness of earthworms in reducing the environmental load of penicillin-related ARGs but also provide insight into the alteration of microbial communities as a potential mechanism. This research contributes to our understanding of the role of earthworms in mitigating the spread of antibiotic resistance and provides valuable insights for the development of strategies to combat this global health issue.

Geotechnical assessments for renewable energy infrastructure: Ensuring stability in wind and solar projects

Geotechnical assessments are crucial for ensuring the stability and longevity of renewable energy infrastructure, particularly in wind and solar projects. This review explores the significance of geotechnical assessments in these projects, highlighting key considerations and challenges. Geotechnical assessments play a critical role in the design, construction, and operation of renewable energy infrastructure, providing essential information about the subsurface conditions that can impact the stability and performance of wind and solar projects. These assessments involve the evaluation of soil, rock, and groundwater conditions to assess their suitability for supporting renewable energy structures. In wind energy projects, geotechnical assessments are essential for determining the foundation design of wind turbines. The soil and rock conditions at the site can significantly impact the stability and load-bearing capacity of the foundation, affecting the overall performance and safety of the turbine. Similarly, in solar energy projects, geotechnical assessments are necessary for designing the foundation of solar panels and support structures, ensuring they can withstand environmental loads and maintain their efficiency over time. One of the key challenges in geotechnical assessments for renewable energy projects is the variability of subsurface conditions. Soil and rock properties can vary significantly over short distances, requiring detailed site investigations to accurately characterize the subsurface conditions. Additionally, the presence of natural hazards such as landslides, earthquakes, and floods can further complicate geotechnical assessments, necessitating robust risk mitigation strategies. Despite these challenges, geotechnical assessments are essential for ensuring the long-term stability and performance of renewable energy infrastructure. By providing valuable insights into subsurface conditions, these assessments help developers and engineers make informed decisions about site selection, foundation design, and risk management, ultimately contributing to the successful implementation of renewable energy projects. In conclusion, geotechnical assessments are vital for ensuring the stability and longevity of renewable energy infrastructure, particularly in wind and solar projects. By providing crucial information about subsurface conditions, these assessments help mitigate risks and ensure the safe and efficient operation of renewable energy projects. Keywords: Geotechnical Assessments, Renewable Energy, Infrastructure, Stability, Wind and Solar Projects.

A method for the fatigue-life assessment of subsea wellhead connectors considering riser wave-induced vibration

During drilling operations, strong non-linear environmental loads are applied to the riser, which can generate powerful fatigue loads, resulting in safety hazards. This paper deals with the problem of the 330 m subsea wellhead connector in the Liu-hua 11–1, which is subjected to long-term non-linear fatigue loading in drilling conditions. Examining the fatigue response law of the subsea wellhead connector ensures the safe operation of offshore oil and gas wells. First, fatigue tests were performed on key components to obtain the stress-fatigue life curve. The F22 strain fatigue life curve was constructed based on the Neuber stress-strain relationship theory and Manson-Coffin strain-life equation. Then, the overall drilling platform - riser - subsea wellhead - soil model was established, and the bending moment-stress data of the subsea wellhead connector was obtained via finite element analysis. Then, the fatigue load spectrum was determined via the MATLAB program using the rainflow counting theory. The response characteristics of the wellhead connector fatigue damage were also compared based on four fatigue damage accumulation theories. A set of fatigue calculation and analysis methods for subsea wellhead connectors was finally developed. This method can provide reference and guidance for subsequent studies.

Adaptive PMSM Control of Ship Electric Propulsion with Energy-Saving Features

Electric ship propulsion is considered one of the most promising alternatives to conventional combustion systems. Its goal is to reduce the carbon footprint and increase a ship’s maneuverability, operational safety, and reliability. The high requirements for ship propulsion make permanent magnet synchronous motors (PMSMs) an attractive solution due to their characteristics. This paper discusses the control problem of a PMSM based on the input–output feedback linearization method combined with the optimal and adaptive control techniques. The method presented here integrates the parameter tuning process with the optimal design of the baseline controller. Since the load disturbances are treated as an additional unknown parameter, there is no need to introduce an integral action to deal with the resulting steady-state error. An important feature of the designed controller is the so-called energetic optimization of the system; i.e., in addition to the aforementioned adaptive and optimal controller, it has a feature of ensuring zero reactive power consumed by the system. The performed simulations of the machine speed stabilization process confirmed the high efficiency of the proposed controller despite the assumed uncertainty of the system parameters and environmental (load) disturbances. Besides achieving high-quality control, an essential feature of this approach is the elimination of the tuning problem.

Intelligent crack identification method for high‐rise buildings aided by synthetic environments

SummaryCracks can develop in high‐rise buildings because of long‐term environmental changes and extreme loading events such as strong winds or earthquakes. Although deep learning‐based identification methods can efficiently identify cracks, the accuracy of crack identification in high‐rise buildings needs to be improved due to the lack of crack datasets specifically related to high‐rise structures. Moreover, the number of available images of cracks in high‐rise is limited. To this end, this paper establishes an intelligent crack identification method based on a photorealistic synthetic modeling technique. First, a computer graphics (CG) model of a high‐rise building with assumed damage is constructed. Subsequently, the CG model is utilized to generate a dataset that includes photorealistic images of the high‐rise building as well as corresponding labels for various components and types of damage. The generated dataset is then used to train a DeepLabv3 + neural network for structural component and damage identification, followed by validation by employing images of both synthetic and full‐scale high‐rise buildings. The trained network can accurately identify different components in images of the full‐scale, high‐rise building and identify cracks that are intentionally synthesized in those images. The results show that the synthetic dataset generated by the CG model not only allows for fast and efficient labeling for the purpose of neural network training but also outperforms methods that do not consider any application‐specific context in crack identification.