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Novel renewable seawater desalination system using hydrogen as energy carrier for self-sustaining community

DESALINATION 2024年 579卷

作者： Wen, Du Kuo, Po-Chih Aziz, Muhammad Univ Tokyo Dept Mech Engn 7-3-1 HongoBunkyo Ku Tokyo 1138656 Japan Univ Tokyo Inst Ind Sci 4-6-1 KomabaMeguro Ku Tokyo 1538505 Japan

This study proposes a novel renewable seawater desalination system in which hydrogen is utilized as an energy carrier to balance the fluctuating electricity supply and demand and provide heat to the desalination system. The proposed system employs a water-hydrogen nexus framework to achieve an efficient operation for providing electricity, potable water, and green hydrogen. The optimal system configuration that considers seasonal variations in renewable energy production is determined by using a heuristic algorithm. It can sustain flexible and standalone operations with less curtailment. The results demonstrate that the system has an average efficiency of 38.9 %, which is higher than the results reported in previous studies. The daily differences in system efficiency are primarily caused by the solar and water electrolysis systems. Curtailment rates of 5 % to 14 % during the operation are owing to the energy storage capacity and supply-demand balance. A higher utilization rate of water electrolysis and fuel cell systems is beneficial for profitability. However, the present utilization rate ranges from 40 %-60 % for water electrolysis systems and <20% for fuel cell systems. Thus, an integrated net-zero system of water electrolysis and fuel cells is proposed, which can be used as a substitute for traditional fossil-based desalination plants.

关键词： Renewable energy Desalination Hydrogen utilization Energy storage Power -to -hydrogen genetic algorithm optimization

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Motorcycle final drive geometry optimization on uneven roads

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MECHANISM AND MACHINE THEORY 2020年 144卷 103647-000页

作者： Alcazara, M. Perez, J. Mata, J. E. Cabrera, J. A. Castillo, J. J. Univ Malaga Dept Mech Engn E-29071 Malaga Spain Univ Jaen Dept Mech & Min Engn Jaen 23071 Spain

The design of transmission systems plays an important role in the dynamic performance of motorcycles. It is well known that power delivery and stability in motorcycles is strongly affected by the geometry of the final drive. This article presents a 2D multibody motorcycle model in which the tire and final drive are considered thoroughly. A nonlinear transient model is used to reproduce forces between the tire and the road. The engine and wheel sprockets, the squat ratio and the chain slack have been taken into account in the final drive kinematic model. The configuration of the final drive elements and its influence on the distance covered by the motorcycle have been studied. Furthermore, the motorcycle final drive design has been optimized to maximize the distance traveled on different uneven roads. Simulations show a superior performance of the motorcycle when the configuration of the final drive elements is optimized. This study contributes to demonstrating the importance of the configuration and geometry of the final drive to improve stability and overall behavior of the motorcycle on uneven roads. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Motorcycle modeling Final drive genetic algorithm optimization Transient tire model

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Terrain-Adaptive Auxiliary Track Tensioning System for Tracked Vehicles

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JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS 2013年第3期8卷 031013-031013页

作者： Matej, Jaroslav Tech Univ Zvolen Dept Forest & Mobile Technol Zvolen 96053 Slovakia

It is known that tension in the track of a tracked vehicle has a large effect on its driving properties. Simple track tensioning solutions, like track adjusting link assembly, use a one-road wheel motion to govern the motion of a track tensioning element. Thus the track tensioning force is a function of a terrain micro-profile. A logical improvement of this approach is to use all of the road wheels to govern the motion of the track tensioning element. This can be achieved by an auxiliary track tensioning system. This paper analyzes the conceptual track tensioning system governed by a terrain micro-profile. The motion of the track tensioning element is designed as a function of all of the road wheels' motions. A genetic algorithm method, implemented in Java language, is used to find the optimal parameters of the tensioning system and the results are verified via multibody dynamics simulation using the MSC. ADAMS/View system. The paper answers the question of whether the use of all of the road wheels' motions to govern the motion of the track tensioning element can be useful or not. The results indicate that the use of the auxiliary system can decrease the variance of the track tensioning force, in comparison with the track tensioning system without auxiliary tensioning. This means that the value of the track tensioning force is closer to its desired, predefined, and constant value during the whole simulation. The tracked vehicle model that is used is a simplified one and it is intended as a base for specific designs of track tensioning systems with auxiliary tensioning. The results suggest that the system can be used to improve the driving properties of tracked vehicles or robots.

关键词： track tensioning tracked vehicle tracked robot genetic algorithm optimization multibody dynamics simulation JGAP java genetic algorithm package MSC ADAMS/View automated dynamical analysis of mechanical system vehicle design track tensioning system tracked robot chassis

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Optimizing a Hybrid Controller for Automotive Active Suspension System by Using genetic algorithms With Two High Level Parameters

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IEEE ACCESS 2024年 12卷 172451-172464页

作者： Tan, Vu Van Tu, Do Trong Vinh, Nguyen Van Thang, Pham Tat Mihaly, Andras Gaspar, Peter Univ Transport & Commun Fac Mech Engn Dept Automot Mech Engn Hanoi 100000 Vietnam Elect Power Univ Fac Mech Automot & Civil Engn Hanoi 100000 Vietnam Hungarian Res Network Inst Comp Sci & Control Syst & Control Lab H-1111 Budapest Hungary

This article presents the in-depth research results concerning the actively controlled suspension system following the Hybrid Active Suspension System (HASS) in vehicles. Initially, detailed introductions are provided for the controller and actuator of this suspension system model. Afterward, the HASS model is proposed for application to the Active Suspension System with integrating Skyhook and Groundhook control methods, wherein a coefficient alpha = 0.3, 0.6, 0.9 is utilized to adjust the correlation between these two models. Through the amplitude transfer function, the transition in enhancing ride comfort and road holding criteria in the HASS is demonstrated. Subsequently, the coefficients of the HASS are optimized through the genetic algorithm optimization with the parameter beta =0.1, 0.5, 0.9, aiming to enhance ride comfort and road holding corresponding to each value of alpha. The simulation and evaluation results utilizing the HASS in both frequency and time domains demonstrate significant improvements in ride comfort and road holding criteria compared to passive suspension systems. Specifically, the ride comfort has improved from 60% to 80%, while the road holding has improved from 10% to 15%. These findings facilitate the development of applications for the controlled suspension system, allowing adaptation to diverse real-world conditions at varying levels.

关键词： Vehicle dynamics and control active suspension system hybrid active suspension system Skyhook model Groundhook model genetic algorithm optimization suspension system Vehicle dynamics and control active suspension system hybrid active suspension system Skyhook model Groundhook model genetic algorithm optimization suspension system

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A Novel Design Method for the Knee Joint of the Exoskeleton Based on the Modular Wearable Sensor

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JOURNAL OF MEDICAL DEVICES-TRANSACTIONS OF THE ASME 2023年第4期17卷 041002-041002页

作者： Cao, Jian Wang, Chang Zhang, Jianhua Li, Kexiang Zhang, Jianjun Hebei Univ Technol Sch Mech Engn Dept Mech Engn Tianjin 300401 Peoples R China Univ Sci & Technol Beijing Sch Mech Engn Dept Mech & Elect Engn Beijing 100083 Peoples R China North China Univ Technol Sch Mech & Mat Engn Dept Mech & Elect Engn Beijing 100144 Peoples R China

This paper innovatively proposes an artificial knee joint customization design scheme based on modular wearable sensors. It aims to solve the compatibility and security problem of wearable devices for different individual knee joints. The method consists of two main parts: measurement and customization. A wearable sensor with three joints is proposed and analyzed. The sensor can measure the kinematic characteristics of human knee joints to obtain the customized design parameters of artificial joints. Designed a bionic four-link knee joint, and the parameters of the connecting rod were optimized by a genetic algorithm based on the measured data. In particular, the measuring device and knee joint are designed in a modular way, and they can be used on the same platform. The modular design method can be used to customize joints for different individuals, which simplifies the difficulty of customization and effectively reduces the cost. After the modular knee joint's optimized design, this paper mainly conducted a number of comparative tests. The comparative test results of three joints show that the dynamic tracking accuracy of customized joints is 54.9% higher than that of ordinary joints and 70.5% higher than that of hinge joints. The results show that personalized customization for individuals can improve human-machine coupling performance.

关键词： custom design genetic algorithm optimization kinematics of the knee joint rehabilitation exoskeleton wearable sensors

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optimization of a hybrid energy plant by integrating the cumulative energy demand

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APPLIED ENERGY 2019年 253卷 113484-000页

作者： Bahlawan, Hilal Morini, Mirko Pinelli, Michele Poganietz, Witold-Roger Spina, Pier Ruggero Venturini, Mauro Univ Ferrara Dipartimento Ingn Via Saragat 1 I-44122 Ferrara Italy Univ Parma Dipartimento Ingn & Architettura Parco Area Sci 181-A I-43124 Parma Italy Karlsruhe Inst Technol Karlsruhe Germany

This paper deals with the optimal design of a hybrid energy plant, which can include the following energy systems: solar thermal collector, photovoltaic panel, hybrid photovoltaic/thermal solar system, combined heat and power system, organic Rankine cycle, absorption chiller, air source heat pump, ground source heat pump and thermal energy storage. Three different configurations are analyzed. In the first configuration, the above-mentioned systems are considered with the exception of the hybrid photovoltaic/thermal solar system and organic Rankine cycle. In the second configuration, a hybrid photovoltaic/thermal solar system is also included and in the third configuration the use of an organic Rankine cycle as the bottoming cycle of the combined heat and power system is evaluated. The optimization goal is to minimize the primary energy demanded throughout the manufacturing and operation phase of the hybrid energy plant. The challenge of non-linear life cycle inventory scaling of energy systems is also addressed. A tower located in northern Italy is selected as a case study and two different approaches are evaluated. The first approach consists of solving the sizing optimization by minimizing primary energy consumption only during the operation phase, while in the second approach primary energy consumption is minimized throughout the life cycle of the plant by integrating the life cycle assessment into the optimization process. The results show that, if life cycle assessment is integrated, the optimal sizes of plant components are different and the primary energy saving throughout the life cycle is always higher. With reference to the LCA integrated approach and compared to the first configuration, the use of a hybrid photovoltaic/thermal solar system instead of separate solar thermal collector and photovoltaic panels is more efficient and may allow a primary energy saving of about 4%. Furthermore, compared to a conventional plant, the primary energy saving achievabl

关键词： Hybrid energy plant genetic algorithm optimization Life cycle assessment Primary energy saving

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Forecast of Coal Demand in Shanxi Province Based on GA-LSSVM under Multiple Scenarios

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ENERGIES 2022年第17期15卷 6475-6475页

作者： Liu, Yujing Du, Ruoyun Niu, Dongxiao North China Elect Power Univ Sch Econ & Management Beijing 102206 Peoples R China

Under the "carbon peaking and carbon neutrality" goal, Shanxi Province adjusts the power supply structure and promotes the development of a high proportion of new energy, which has a certain impact on the demand for thermal coal. Therefore, constructing a reasonable forecasting model for thermal coal demand can play a role in stabilizing coal supply and demand. This paper analyzes various factors related to coal demand, and uses Pearson coefficient to screen out six variables with strong correlation. Then, based on the scenario analysis method, combined with the "14th Five-Year Plan" of Shanxi Province, different scenarios of economic development and carbon emission reduction development are set. Finally, a multi-scenario GA-LSSVM forecasting model of thermal coal demand in Shanxi Province is constructed, and the future development trend of thermal coal demand in Shanxi Province is predicted. The results show that the demand for thermal coal is the largest in the mode of high-speed economic development and low emission reduction, and the demand for thermal coal is the lowest in the mode of low-speed economic development and strong emission reduction, which provides a scientific basis for the implementation of Shanxi Province's thermal coal supply policy.

关键词： coal demand forecast scenario analysis least squares support vector machine genetic algorithm optimization

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genetically Optimized Pitch Angle Controller of a Wind Turbine with Fuzzy Logic Design Approach

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ENERGIES 2022年第18期15卷 6705-6705页

作者： Pehlivan, Ahmet Selim Bahceci, Beste Erbatur, Kemalettin Sabanci Univ Fac Engn & Nat Sci Mechatron Engn TR-34956 Istanbul Turkey

An important engineering challenge is the design of a wind turbine's pitch angle controller. The dependability, safety, and power output maximization of a wind turbine are all impacted by this controller. In this study, a 2 MW doubly fed induction generator wind turbine's blade angle controller design with a novel fuzzy logic controller is tested in a simulated environment. The evolutionary algorithm technique is used to optimize the fuzzy logic controller with three inputs. A genetic algorithm is used to optimize the specified pitch angle controller for a number of coefficients. After the optimization process, the controller's performance is assessed in terms of power output, overshoot, and steady-state error characteristics.

关键词： wind energy wind turbine pitch angle controller genetic algorithm optimization fuzzy logic

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Optimal design of Multiresonant Layered Acoustic Metamaterials (MLAM) via a homogenization approach

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ENGINEERING STRUCTURES 2023年第1期293卷

作者： Sal-Anglada, G. Yago, D. Cante, J. Oliver, J. Roca, D. Ctr Int Metodes Numer Engn CIMNE Campus Nord UPC Ed C1C-Gran Capita S-N Barcelona 08034 Spain Univ Politecn Catalunya Barcelona Tech UPC Escola Super Enginyeries Ind Aerosp & Audiovisuals Campus Terrassa UPC C-Colom 11 Terrassa 08222 Spain Univ Politecn Catalunya BarcelonaTech UPC Escola Tecn Super Enginyers Camins Canals & Ports Campus Nord UPC Ed C1C-Jordi Girona 1 Barcelona 08034 Spain

Broadband sound attenuation at low frequency ranges (below 500 Hz) has been a challenge in the acoustics field which cannot be solved, via conventional materials, unless impractical amounts of mass are employed. Multiresonant Layered Acoustic Metamaterials (MLAM) offer exceptional attenuating properties at lower frequencies, through novel coupled resonances mechanisms, in a layered configuration that make them amenable for large-scale manufacturing. To show the potential capabilities of MLAM, a novel computational design strategy has been developed to optimize the metamaterials' performance in terms of their Sound Transmission Loss (STL). First, a multiscale homogenization framework specifically derived for MLAM allows an accurate and extremely fast evaluation of their STL response to normal-incidence acoustic waves in the frequency range of interest. Then, the MLAM design is parameterized into a set of relevant geometric features, which are optimized by means of an optimization scheme based on standard genetic algorithms combined with the homogenization model. The results demonstrate how this design strategy is a powerful tool to obtain optimal MLAM panel designs subject to constraints imposed by the application, for instance, in terms of weight or thickness of the panel, or the manufacturing process (e.g. geometric tolerances).

关键词： Acoustic metamaterials Coupled resonances MLAM Computational homogenization genetic algorithm optimization

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Fuzzy-decision tree modeling for H2S production management in an industrial-scale anaerobic digestion process

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BIOCHEMICAL ENGINEERING JOURNAL 2024年 208卷

作者： Rahimieh, Armin Mehriar, Milad Zamir, Seyed Morteza Nosrati, Mohsen Tarbiat Modares Univ Fac Chem Engn Biochem Engn Dept Tehran Iran

H2S is a byproduct in anaerobic digesters (ADs), causing significant challenges due to its negative impact on biogas quality and equipment corrosion. As a solution, previous researchers developed complex mechanistic models that are computationally expensive due to solving equations with many variables. These models were only tested within normal H2S ranges. This research introduces a novel hybrid fuzzy-decision tree (F-DT) model to predict H2S production from primary/secondary sludge ratio (P/S), dry solids (DS), and volatile solid (VS) reduction parameters in the Qom wastewater treatment plant in Iran. Notably, the H2S concentrations in this facility consistently surpass the acceptable thresholds reaching levels as high as 6500 ppm, in contrast to the designed accepted limit of 3000 ppm. The process involved collecting and pre-processing data, creating a decision tree classifier for rule generation, developing a fuzzy model suited for complex systems like AD, and optimizing it with a genetic algorithm. The analysis of the final model revealed that the P/S ratio significantly influences elevated H2S levels, indicating that maintaining a P/S ratio > 1.2 holds promise as an effective strategy. The model is both simple and interpretable, with decent accuracy in predicting H2S compared to previous models. This study not only introduces a useful method for optimizing industrial-scale ADs, but also aims to uncover the reasons behind high H2S levels.

关键词： Anaerobic digestion Decision tree Fuzzy logic genetic algorithm optimization Hybrid modeling Hydrogen sulfide

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