Layout Optimization Research Articles

Semi-Empirical Model Based on the Influence of Turbulence Intensity on the Wake of Vertical Axis Turbines

In the context of energy shortages and the development of new energy sources, tidal current energy has emerged as a promising alternative. It is typically harnessed by deploying arrays of multiple water turbines offshore. Vertical axis water turbines (VAWTs), as key units in these arrays, have wake effects that influence array spacing and energy efficiency. However, existing studies on wake velocity distribution models for VAWTs are limited in number, accuracy, and consideration of influencing factors. A precise theoretical model (Lam’s formula) for wake lateral velocity can better predict wake decay, aiding in the optimization of tidal current energy array designs. Turbulence in the ocean, serving as a medium for energy exchange between high-energy and low-energy water flows, significantly impacts the wake recovery of water turbines. To simplify the problem, this study uses software ANSYS Fluent 2020 R2 for two-dimensional simulations of VAWT wake decay under different turbulence intensities, confirming the critical role of turbulence intensity in wake velocity decay. Based on the obtained data, a new mathematical approach was employed to incorporate turbulence intensity into Lam’s wake formula for VAWTs, improving its predictive accuracy with a minimum error of 1%, and refining some parameter calculations. The results show that this model effectively reflects the impact of turbulence on VAWT wake recovery and can be used to predict wake decay under various turbulence conditions, providing a theoretical basis for VAWT design, optimization, and array layout.

Efficient layout optimization of offshore wind farm based on load surrogate model and genetic algorithm

Wind farm layout optimization (WFLO) has become a significant approach to enhancing the efficiency of wind energy utilization. However, load also represents a critical factor that must be considered during optimization. To enhance power generation while controlling loads within limitations, an innovative load-constrained layout optimization method that employs a surrogate model based on artificial neural networks and genetic algorithms was proposed. This paper verified the accuracy of the surrogate model and then conducted layout optimizations on a single and a full wind condition case to assess the proposed method. The results indicated that the mean absolute percentage errors of load channels can meet the precision requirements for WFLO. A comparison of layout optimization results between the method proposed in this paper and the traditional method showed that in the single-wind-condition case, the method proposed in this paper reduced the maximum load by 5.64 % compared to the traditional method, with nearly identical power output; in the full-wind-condition case, the reduction of maximum load was 1.70 %, while only sacrificing the annual power generation by 0.10 %. This study provides a load-constrained WFLO method, promising to effectively ensure the lifespan of wind turbines while increasing power generation and offering significant engineering value.

Development and validation of a three-dimensional wind-turbine wake model based on high-order Gaussian function

Under natural conditions, the wake velocity distribution approximates top-hat shape in the near wake center, and a Gaussian shape in the far wake. To improve the prediction accuracy of the wake distribution, this paper proposes a three-dimensional high-order Gaussian linear entrainment wake model by modifying the wake velocity distribution with high-order Gaussian function. Field tests and wind tunnel tests are then conducted. The obtained results show that the proposed model can accurately describe the radial and vertical spatial distributions of the wake flow. Under different wind speeds, the maximum and minimum radial relative errors are respectively 7.29% and 1.4%, while the maximum and minimum vertical relative errors are respectively 7.64% and 3.87%. This demonstrates that the proposed model can accurately predict the velocity distribution in the whole wake region. The proposed model is simple, has low cost, and exhibits high accuracy. Thus, it can be used in wind farm layout optimization and wake control.

Calculation method of temporary cable force in incremental launching construction of large span steel box girder without auxiliary pier

The Fenshui River Bridge is a steel–concrete composite girder bridge with a main span of 90 m. Due to the topographical constraints, the steel box girder was constructed without the use of auxiliary piers, employing incremental launching techniques. This article focuses on the construction technology used for the steel box girder of the Fenshui River Bridge. Firstly, using the influence matrix method, the cable force is determined based on the maximum cantilever state of the structure, with the vertical deformation of the front end of the guide beam and the horizontal deformation of the top of the tower as the control objectives. The unstressed cable length is then calculated based on the mechanical relationship between cable deformation and cable force. A calculation method for adaptive cable force is proposed, which is based on the variation of the stress-free cable length within the adaptive structural system. Next, the finite element analysis method was employed to determine the optimal layout position for the tower. The results indicate that during the incremental launching construction of the steel box girder, the calculated cable forces using the method proposed in this paper are in close agreement with the measured cable forces. At the maximum cantilever state of the structure, the calculated and measured values of the cable force resulted in a percentage difference of 3.96%. The calculated values of deformation and stress in key sections showed a percentage difference of 6.4% for deformation and 6.6% for stress. To maximize the effectiveness of the tower and cable, the tower should be positioned above the bridge pier when the guide beam crosses the maximum span. The findings of this paper can serve as a reference for the construction of similar types of bridges.

Chemical plant optimization layout based on the domino hazard index considering the fixed hazard unit outside the available area

The layout of chemical plants is a significant step to promote the safe and efficient operation of a chemical factory. In the actual production process, the chemical process plant layout may be affected by immovable hazards outside the available layout area. In this paper, the external hazard unit is arranged as one of the chemical process plants. The domino effect potential of all chemical process plants is quantified by using the classical domino hazard index (DHI). A layout optimization model considering the effects of external hazard units has been proposed to obtain the optimal plant layout from economic and safety aspects. The feasible layout solutions are obtained under the orientation, boundary and non-overlapping constraints by the non-dominated sorting genetic algorithm II (NSGA-Ⅱ). The proposed model is further analyzed through a hypothetical case of three storage tanks outside the acrylic acid (AA) production plant layout area. The results show that the total cost range for the optimal solution is 650348–1365443 $, with corresponding DHI values ranging from 29 to 129. The plant with larger DHI value will be arranged to far away from the external hazard units to obtain a safer layout. This work can provide rational layout solutions for the layout designers to make different decisions according to the actual situation.

Optimization of wind farm layout to maximize the energy yield

Over time, the use of wind turbines has evolved in terms of the size and number of the turbines. The change in wind turbines comes as a result of major structural changes and then an increase in their production capacity. In the framework of the most stable operation for the surface of the terrain used in this study, a series of configurations have been proposed that are directly related to technical and economic sustainability. The complete scenarios will be realized in Koznica, where one-year measurements are done. In the framework of the realized scenarios, it can be seen that there is variability in terms of energy output from these configurations, which maximally comes from wake losses caused by the terrain. In cases where the scenarios with the addition of small turbines are studied, they, in the technical aspect, affect the increase in energy production, which, if those turbines were not installed, would not be applied. As an important part, the economic aspect of the realization of the previous optimization scenarios is analyzed by using Monte-Carlo simulation for LCOE analysis. Thus, it can be concluded that the analyzed scenarios with the addition of small turbines in the optimization process are more suitable and feasible for implementation.

Towards sustainable energy: integrating ERA5 data for offshore wind farm planning in India

India’s pursuit of offshore wind energy development, particularly along the Tamil Nadu coastline within its Exclusive Economic Zone (EEZ), faces significant spatial and economic challenges due to existing industrial activities and water depth limitations. Motivated by the need to optimize offshore wind resources and bridge the gap between onshore and offshore wind energy achievements, this study hypothesizes that ERA5 reanalysis wind data can be relied upon for assessing offshore wind resources and optimizing wind farm layouts, especially in the absence of measured data. The research employs methods such as comparing ERA5 data with empirical wind measurements, generating wind rose diagrams for layout optimization, and conducting a comprehensive financial analysis to estimate the Levelized Cost of Energy (LCoE). The results confirm the efficacy of ERA5 data, identifying an optimal wind farm layout with a capacity density of 5.17 MW per square kilometer, turbine spacing of 7.22 meters, and an LCoE of Rs. 8.84 per kWh. The study concludes that significant financial support and strategic policy interventions are essential for minimizing wake losses, optimizing capacity density, and fostering the long-term growth of India’s offshore wind energy sector, providing critical insights for policymakers, developers, and investors. The novelty of this research lies in its detailed exploration of spatial optimization and cost-effective strategies to enhance the techno-economic viability of offshore wind projects in India.

Optimization of territorial space layout in China

Optimization of territorial space layout in China

Study on Optimization of Land Use Structure in Fujian Province Based on Low-Carbon Perspective

Carbon peaking and carbon neutrality strategies are pivotal in addressing climate change. Optimizing land use structure is a fundamental approach to achieving low-carbon development within a given territory. This study focuses on Fujian Province as the research subject, predicting carbon emissions for the next decade by analyzing the correlation between land use types and carbon emissions using the gray model. This analysis is based on land use panel data spanning from 2007 to 2021. The study applies the FLUS-Markov model to simulate Fujian’s land use in 2030. A multi-objective optimization model is developed from a low-carbon perspective, integrating carbon emissions, economic, and ecological factors. The study explores land use under three scenarios: natural development scenario (NS), low carbon scenario (LCS), and comprehensive scenario (CS). Findings highlight the relationship between land use-related carbon emissions, urbanization, and relevant policies in Fujian. The FLUS-Markov simulations suggest that under the NS scenario, carbon emissions in 2030 will reach 77.829 million tons, an increase of 11.013 million tons from 2020. In contrast, the LCS demonstrates that optimizing land use structures can effectively balance carbon reduction, economic growth, and ecological preservation. Under the CS, 2030 emissions could be reduced by 7.2854 million tons while maintaining economic and ecological benefits. Despite variations in construction land expansion across these scenarios, all follow a “one belt, one core” development pattern. The study concludes with policy recommendations, including industrial layout optimization and clean energy promotion. These findings support the alignment of land use optimization with Fujian’s future development needs, offering guidance for land-use planning and policies focused on low-carbon objectives.

Study on heat transfer performance of cooling channels in proton exchange membrane fuel cells based on topology optimization

Based on topology optimization method, a dual-objective function topology optimization model containing minimum average temperature and minimum flow power dissipation was established in this study. Coupled with the uneven heat generation model of proton exchange membrane fuel cells, the optimal layout scheme under the target operating conditions was adaptively obtained. The effects of volume fraction, objective function weight, and parabolic inlet velocity on the flow channel structure and cooling performance of topological cooling plates were studied. The results indicate that with the increase of volume fraction, the area of fluid region increases, the average temperature and the pressure drop of cooling plate gradually decrease. At the volume fraction of 0.5, the cooling plate has the best cooling performance. The temperature difference and maximum temperature reach the minimum values of 5.45 K and 347.58 K, respectively. When the volume fraction increases from 0.4 to 0.6, the pressure difference decreases by 67.64 %. With the increase of temperature weight coefficient, the area of high-temperature area gradually decreases, and the temperature uniformity is significantly improved. When the inlet velocity of coolant is 0.025 m/s and the temperature weight coefficient is 0.9, the average and maximum temperatures of cooling plate reach the lowest values, which are 343.53 K and 344.51 K, respectively. The maximum temperature of cooling plate under parabolic inlet velocity is of 347.87 K, which is 0.29 K higher than that under uniform inlet velocity. Non-uniform coolant inlet velocity will lead to a decrease in heat transfer capacity of cooling plate and an increase in coolant power consumption.

A miniaturized on‐chip BPF with low insertion loss and wide stopband based on integrated passive device technology

AbstractIn this study, a novel bandpass filter (BPF) characterized by low insertion loss (IL) and the presence of two transmission zeros (TZs) based on integrated passive device (IPD) technology is introduced. The design incorporates a low‐pass filter and a high‐pass filter which both exhibit strong out‐of‐band suppression performance. The control structure for TZs is constructed by cascading the inductance and capacitance components. The TZ controlling structure primarily generates TZs at high frequencies, resulting in a further bandwidth enhancement in the stopband. The lumped circuit of the proposed BPF is first constructed, and rigorous design formulas are provided to assist in constructing the proposed design. After schematic optimization, the second step involves layout optimization and simulation based on the specific IPD process. Experimental results mounted on a printed circuit board demonstrate that the bandwidth spans from 3.3 to 4.2 GHz with an IL of only 2.0 dB at the center frequency. Additionally, this BPF achieves impressive sideband suppression, exceeding 18 dB in the 0–1.7 GHz range and 30 dB in the 9–15 GHz range. Remarkably, the BPF is exceptionally compact with only 0.5 mm × 1.0 mm (0.006λc × 0.012λc). The proposed BPF exhibits outstanding performance with minimal IL and extensive sideband suppression at such a compact size based on the IPD technology.

Warehouse layout optimization for fishbone robotic mobile fulfillment systems

The rapid development of electronic commerce has increased demands for order fulfillment efficiency, making this a crucial challenge for warehouse systems. The study proposes a novel fishbone robotic mobile fulfillment system (FRMFS) to optimize warehouse layout and enhance the picking efficiency of automated warehouse systems, such as robotic mobile fulfillment systems (RMFS). Through the construction and analysis of mathematical models, the research demonstrates that FRMFS can significantly reduce the travel distance of robots when compared to traditional RMFS. This leads to an improvement in the overall picking efficiency of the warehouse system. The study also examines the impact of warehouse parameters, cross-aisle angles, and the number of picking stations on system operational efficiency. Simulation experiments confirm that FRMFS can reduce picking distances by 18%–28% compared to traditional RMFS. This makes it particularly suitable for complex warehouse systems with high requirements for operational response time and system throughput. Furthermore, the study introduces a point-based layout design method for picking stations in FRMFS, demonstrating its efficiency as a heuristic approach. This research presents a scientific analysis framework and model support for the operational design and optimization of FRMFS, offering valuable insights for management practices.

Exploration of the Indoor Layout Optimization Model in Computer-Aided Visual Analysis

Exploration of the Indoor Layout Optimization Model in Computer-Aided Visual Analysis

Layout Optimization of Visual Communication Design Based on Particle Swarm Optimization Algorithm

Layout Optimization of Visual Communication Design Based on Particle Swarm Optimization Algorithm

The application of deep learning technology in integrated circuit design

This study addresses the intricate challenge of circuit layout optimization central to integrated circuit (IC) design, where the primary goals involve attaining an optimal balance among power consumption, performance metrics, and chip area (collectively known as PPA optimization). The complexity of this task, evolving into a multidimensional problem under multiple constraints, necessitates the exploration of advanced methodologies. In response to these challenges, our research introduces deep learning technology as an innovative strategy to revolutionize circuit layout optimization. Specifically, we employ Convolutional Neural Networks (CNNs) in developing an optimized layout strategy, a performance prediction model, and a system for fault detection and real-time monitoring. These methodologies leverage the capacity of deep learning models to learn from high-dimensional data representations and handle multiple constraints effectively. Extensive case studies and rigorous experimental validations demonstrate the efficacy of our proposed deep learning-driven approaches. The results highlight significant enhancements in optimization efficiency, with an average power consumption reduction of 120% and latency decrease by 1.5%. Furthermore, the predictive capabilities are markedly improved, evidenced by a reduction in the average absolute error for power predictions to 3%. Comparative analyses conclusively illustrate the superiority of deep learning methodologies over conventional techniques across several dimensions. Our findings underscore the potential of deep learning in achieving higher accuracy in predictions, demonstrating stronger generalization abilities, facilitating superior design quality, and ultimately enhancing user satisfaction. These advancements not only validate the applicability of deep learning in IC design optimization but also pave the way for future advancements in addressing the multidimensional challenges inherent to circuit layout optimization.

Precise Positioning of Distributed Power Supply in Smart Microgrids for High-latitude Areas

This paper focuses on the precise micro-location of distributed power sources in smart microgrids at high latitudes. It first clarifies the strategic position of microgrids in power systems, especially in complex environments at high latitudes, and emphasizes the urgency of their location. Subsequently, it systematically reviews the research trends of smart microgrid and distributed power supply domestically and internationally, revealing the limitations of existing research and problems to be solved. The unique climate adaptability and power supply-demand characteristics of microgrids in this region are deeply analyzed according to the characteristics of high latitude, clarifying the key role of distributed power supply. The core discussion revolves around examining the application potential and limitations of mainstream distributed energy sources such as solar energy, wind energy, and energy storage devices in a specific environment. The aim is to provide a theoretical basis and practical guidance for scientific planning and optimal layout of smart microgrids in high-latitude regions while promoting innovation and development in this field.

A Review on Application of Pin-Fins in Enhancing Heat Transfer

The pin-fin is one of the main technologies in enhancing heat transfer. The accelerated flow and vortex structures are produced, which can disrupt the development of the flow boundary layer. The configuration of the pin-fin is obvious for heat transfer and flow characteristics, including its shape, size, and arrangement in the cooling channel. This work provides a detailed introduction to the application of pin-fins in enhancing heat transfer and reducing flow resistance, including the conventional shapes, improved shapes based on circular pin-fins and irregular shapes. At the same time, the influence of the diameter, height and density of pin-fins on heat transfer and flow performance is studied, and the influence mechanism is analyzed from the perspective of boundary layers. In addition, some applications that combine pin-fins with other cooling methods to further improve performance are analyzed. In terms of the optimization technology, the structure optimization for pin-fin shape and the layout optimization for pin-fin array are summarized. Therefore, this review provides a wide range of literature for the design of internal cooling channel pin-fins.

Research on the division of heat dissipation spaces for multiple heat sources based on the adiabatic characteristic of heat flow lines

Due to the pressing need for compact layouts, the spacing between high-power devices is gradually decreasing, making the mutual influence between multiple heat sources unavoidable. Therefore, this paper proposes a method based on the adiabatic characteristics of heat flow lines and their convergence positions to evaluate the rationality of the thermal space design of each heat source. This method has been validated for applicability in one-dimensional, two-dimensional, and three-dimensional multi-heat-source conjugate convection heat transfer. Heat flow lines have significant advantages in describing energy flow, as they align with the direction of the temperature gradient. In thermal spaces with adiabatic boundaries or mutual influences between multiple heat sources, heat flow lines converge at certain positions. The relationship between adiabatic boundaries and heat flow line convergence positions has been studied, and a more interpretative decoupling scheme for multi-heat-source systems has been proposed. The main feature of this scheme is the separation of each heat source in the same steady-state thermal space and assigning adiabatic boundaries to the solid partition surfaces, allowing efficient observation of the thermal conditions of individual heat sources and targeted layout optimization. Results indicate that this method can utilize changes in heat flow line convergence positions to assess current thermal conditions and can be used to compare the thermal performance of different shaped heat sinks. Simulation results show that under the same mass conditions, thin-fin heat sinks perform 47 % better than thick-fin heat sinks, providing a more comprehensive and intuitive assessment compared to metrics such as thermal resistance and average temperature. The proposed method offers new ideas for multi-heat-source layout optimization, heat flow control, multi-heat-source partitioned simulation, and abnormal heating detection in multiple heat sources.

Optimization Method of Floating Fixture Layout for Distortion Control of Low-Stiffness Thin-Walled Beams.

The aim is to reduce the elastic deformation of the web and side walls of low-stiffness thin-walled beams when the floating fixture method is used. This paper takes the number and position of fixture points as the optimization variables, establishes a calculation model of elastic deformation, and constructs the objective function of maximum total elastic deformation. An optimized solution utilizing the augmented multiplier method is employed, which forms the basis for the fixture layout optimization method to reduce the elastic deformation of low-stiffness thin-walled beams. A theoretical calculation, simulation analysis, and the fixture layout optimization of total maximum elastic deformation were completed using an aluminum alloy low-stiffness thin-walled beam as an example. The results show that based on the optimized layout, the average relative error between the calculated value and the simulated value of total maximum elastic deformation is 17.43%, and the simulated value of maximum elastic deformation is reduced by 48.49% after optimizing the fixture layout. The measured value is reduced by 0.02 mm on average, and deformation is reduced by 74.07%, which verifies the effectiveness of the floating fixture layout optimization control of machining elastic deformation proposed in this paper.

Multi-modal control and position optimization of solar panels

This paper investigates the impact of the position of piezoelectric actuators on the vibration control effect of the membrane plane composed of solar sail materials with a given unit area. Firstly, the nonlinear vibration equation of the membrane structure is perfected based on the system equation established by Yifan Lu et al. Then, the modal coupling effect pointed out by Liu Xiang is considered, and the fourth-order modal displacement generated by the piezoelectric actuator in vibration control is derived. Subsequently, the sliding mode controller used in vibration control is designed based on Lyapunov stability theory, and its effectiveness is verified through Simulink simulation. The sliding mode controller is used to calculate the required excitation signal and apply it to the piezoelectric patches. The reverse force is generated through the inverse piezoelectric effect of the patches to actively suppress the vibration of the solar sail. By changing the position and size of each piezoelectric actuator on the solar sail plane, this paper compares the impact of different layout positions on vibration control, and proposes an optimal layout scheme for the position of the piezoelectric patches in terms of control effectiveness.