Optimal Design Scheme Research Articles

Flexibility index for a distributed energy system design optimization

Flexibility plays a critical role in the design of distributed energy systems (DESs) as it encompasses various aspects related to demand, storage, and supply. To optimize the capacity configuration of DESs effectively, a novel flexibility index (FI) is proposed in this study. The FI is constructed based on the fuzzy best-worst method with considerations for economy, autonomy, energy efficiency, and environmental friendliness, aligning with the characteristics of the DES. Considering FI, particle swarm optimization is employed to determine the optimal design scheme for the DES. A case study involving a swimming pool in Changsha City is conducted to demonstrate the reliability of the proposed optimization scheme. Furthermore, a multi-objective optimization model based on non-dominated sorting genetic algorithm-II and technique of ordering preferences for ideal solution similarity algorithms is developed with different objective functions. The results show that the system optimized considering flexibility maintains better performance, with system flexibility, renewable energy penetration, and off-grid degree indices of 0.824, 0.780, and 0.757 respectively. In addition, the optimization of system configuration considering flexibility can dynamically respond to diverse energy demands, maintaining lower operation and maintenance costs ($11223.75 per year), and lower CO2 emissions (91800kgCO2 per year). The quantified FI presented in this study provides a user-friendly and reliable optimization index for the design of DESs.

Design optimization of energy systems for zero energy buildings based on grid-friendly interaction with smart grid

Zero-energy buildings usually achieve annual net-zero energy balance by generating electricity using on-site renewable energies and interconnecting with the power grid. However, the impact of energy mismatch problem in zero-energy buildings design on the grid is often overlooked, which potentially compromises grid's stability. To address this issue, this paper presents an optimization design method based on "grid-friendly interaction" which optimizes the energy system of zero-energy buildings to ensure better alignment between the building's electricity purchase/sale and grid demand. In this study, an indicator of "grid-friendly interaction", which represents the ratio of the net building friendly interaction power to the total annual interaction power, is firstly established to guide buildings in improving their interaction with the grid. Next, the energy supply, demand, and storage schemes of renewable energy systems in the zero-energy building are iteratively adjusted to achieve the best match with grid's expectations. This optimization design method was applied to a practical case in Hong Kong. Results show that, compared to the benchmark building, the optimal system design scheme increases grid friendliness by 83 %, reduces carbon dioxide emissions by 77 %, but also incurs a total cost increase of 180 %. The optimization design method proposed in this paper can effectively mitigate the impact of zero-energy buildings on the power grid, fostering enhanced interplay between the building structures and the grid. The study significantly contributes to the advancement of exploring the potential for energy flexibility in zero-energy buildings, which is of great significance for the safe and stable operation of future grids. The purpose of this study is to explore the energy flexibility potential of zero-energy buildings, which is of great significance for the safe and stable operation of future grids.

Design and performance evaluation of a novel metamaterial broadband THz filter for 6G applications

Terahertz (THz) radiation, which has applications in the imaging of objects, non-destructive testing, satellite communication, medical diagnostics, and biosensing, has generated a great deal of attention due to its remarkable properties. This paper proposes a novel broadband filter for THz applications. The main idea is to overcome the insertion loss and bandwidth issues by modeling a frequency-domain finite difference method and guided-mode resonance (GMR). The optimal design scheme of the wideband pass filter based on the circular resonant ring is discussed by comparing the transmission parameters under various parameters. This scheme overcomes the restriction of the narrow passband bandwidth of the prior THz filters and achieves approximately 3 dB bandwidth of 0.54 THz. The proposed THz filter paper also has the advantages of a straightforward structure, low processing costs, and ease of conformal with other structures, and it can be used for stealth fighters, new communication technology, and precise instruments. In addition, when compared to existing models, the suggested filter offers higher 3 dB BW operation, increased transmittance, low insertion loss, and stable performance at various oblique angles.

Microstructure design and optimization of high-sensitivity interdigital capacitive humidity sensor based on uncertainty analysis

The microstructure of the interdigital capacitive humidity sensor plays a critical role in achieving high sensitivity in measurements. Performing a quantitative evaluation to assess the influence of structural parameters on sensor sensitivity is vital for improving the overall performance of the sensor. In this paper, a theoretical mathematical model and a structural uncertainty propagation model are developed for the interdigitated capacitive humidity sensor, considering the uncertain errors that occur during the processing and measurement processes. A quantitative analysis is conducted to investigate the impact of each structural component and its corresponding uncertainty on the output sensitivity. Moreover, by integrating the two constructed models, the paper formulates an optimal equation for sensor performance that mitigates the impact of structural errors on the system while improving sensor sensitivity. Researchers have the flexibility to adjust sensor material, environmental conditions, structural components, and other parameter variables within the model, according to specific application requirements, to achieve the optimal design scheme for a sensor with specific materials and structure. The proposed method and model presented in this article have undergone verification using finite element physical simulation. The sensitivity model achieves an accuracy rate of 94.45%, whereas the uncertainty model achieves an accuracy rate of 81.96%. Additionally, the model reduces the calculation time to 1/550th and the required computational resources to 1/5th of the simulation, thereby greatly improving the efficiency of sensor optimization design.

Multi-objective and machine learning strategies for addressing the Water–Energy–Waste nexus in the design of energy systems

This paper presents a multi-objective strategy coupled with fuzzy C-means to address synergies and conflicts around the water–energy–waste nexus. The proposal deals with an optimal design and operation scheme in a multi-objective framework where the objective functions are linked to the nexus. The objective functions are normalized to obtain subsets of functions that are used to assess the performance of the nexus and compute trade-off optimal solutions. The soft clustering algorithm is used to determine levels of synergy among Pareto optimal solutions. The proposed strategy has the potential to address problems with many-objective functions, in which the Pareto front has representation limitations, allowing for the identification of conflicts. The soft clustering algorithm indicates different levels of synergy among the Pareto optimal solutions based on the level of membership. The focus of the analysis is on distributed generation systems. As a demonstration, the coupling of a combined heat and power unit with a biodigester and a thermal storage system, interconnected to the local grid. The objective functions, used as descriptors of the nexus, are the use of waste, energy efficiency and water consumption, which are used with the economic performance of the system to configure a problem of many-objective functions.

Heat transfer analysis and structure optimization of unit of flat plate based on a response surface test: An experimental teaching perspective in higher education

The Flat Plate is a common component of solar photothermal experiment and an important teaching tool in the new energy teaching experiment. Aiming at the problem of low heat transfer efficiency and poor teaching effect of traditional roll-bond flat plate, this paper conducts a numerical simulation study on the flow and heat transfer characteristics in the ”Y” -shaped channel unit. The four parameters of width, length, runner parting angle and runner width are used as control variables to optimize the heat transfer structure of the runner. Taking the ”Y” -shaped channel unit as the research object, the finite element model of conjugate heat transfer was established by using Fluent. Through numerical simulation analysis, it is concluded that in the defined length and width interval, the thermal efficiency increases first and then decreases with the increase of the length of the heat transfer unit, and the pressure drop coefficient has a negative correlation with the length and width of the unit. The runner width has a positive correlation with the thermal efficiency and a negative correlation with the pressure drop coefficient. Then, according to the Box-Behnken principle, a response surface test for heat transfer optimization was designed, an optimization model with thermal efficiency and pressure drop coefficient as the response indicators was established, and the optimal element design scheme was determined. The optimization results show that when the subunit length of the heat transfer runner is 40 mm, the width is 35 mm, the parting angle is 60°, and the runner width is 11 mm, the thermal efficiency of the ”Y”-shaped runner is 0.782, and the pressure drop coefficient is 0.121. Finally, a direct-expansion solar auxiliary heating system is built to test the scheme. The experimental results show that the collector using the ”Y”-shaped channel shows better solar energy utilization, which increases the COP of the system by 15.2%. This study provides a reference for the design and optimization of other types of flow channels to improve the heat transfer efficiency of the roll-bond flat plate. Through optimization, the system has innovated in the experimental mode, effectively made up for the shortcomings in the training of new energy professionals, and enriched and developed the experimental theory system and teaching methods of higher education of energy and power majors.

Multi-objective optimization design of coupled wall structure with hybrid coupling beams using hybrid machine learning algorithms

A new hybrid coupling beam incorporating buckling restrained energy dissipaters and viscous dampers was previously recommended. The beam can effectively reduce the floor acceleration and interstory drift ratio of coupled wall structure, and has great application prospects. However, the optimal design of a structure with hybrid coupling beams needs to consider multiple objectives, and these objectives often conflict with each other. At the same time, multiple parameters need to be optimized, resulting in a corresponding increase in the time-cost. This usually brings challenges to structural design. To address this issue, this study presents a hybrid intelligent optimization framework based on multi-objective particle swarm optimization (MOPSO) and machine learning techniques. The developed framework uses machine learning technology to quickly predict the seismic performance of structures with hybrid coupling beams, and obtain a design solution set through multi-objective particle swarm optimization. The proposed framework is demonstrated by considering a case study of a 12-story coupled wall structure with hybrid coupling beams, and it is shown that compared with the initial stage of optimization, the seismic performance of optimized structure is simultaneously improved at close cost. The floor acceleration and interstory drift ratio of the optimized structure are reduced by 11.5% and 38.7%, respectively. Finally, a formula is proposed to quantify the optimization result of pareto solution, so as to make an optimal structural design scheme. In practice, the proposed framework can provide guidance for realizing rapid and accurate about multi-objective optimization of the coupled wall structure with hybrid coupling beams.

Comparative studies and optimizations of air distribution of underground building ventilation systems based on response surface methodology: A case study

As underground enclosed buildings, utility tunnels have limited ventilation conditions. An efficient ventilation system is necessary for improving the indoor thermal environment and air quality in utility tunnels. In this paper, exhaust fan ventilation (EFV), relay fan ventilation (RFV), and innovative wall-attached ventilation (WAV) schemes are compared using a series of evaluation indicators (i.e., energy efficiency coefficient, nonuniform coefficient, temperature not guaranteed rate, and age of air). The results show that the WAV scheme offers a higher ventilation efficiency, while decreasing the age of air and providing a uniform air distribution. Thus, the WAV scheme is recommended for utility tunnel ventilation systems. Additionally, the WAV scheme is further optimized and analysed based on response surface methodology (RSM). The influence of different factors (i.e., the slot outlet height (h), slot outlet width (b), air-supply velocity (u0), and cable heat source intensity (q)) on the evaluation indicators is studied, and the optimal design scheme (h = 1.40 m, b = 0.12 m, u0 = 3.00 m/s, q = 74.5 W/m2) is obtained and verified. The age of air in the optimal design scheme is 486.50 s. This paper can provide a reference for the ventilation design of urban underground buildings.

Thermal Analysis and Optimization of Energy Storage Battery Box Based on Air Cooling

For energy storage batteries, thermal management plays an important role in effectively intervening in the safety evolution and reducing the risk of thermal runaway. Because of simple structure, low cost, and high reliability, air cooling is the preferred solution for the thermal management. Based on a 50 MW/100 MW energy storage power station, this paper carries out thermal simulation analysis and research on the problems of aggravated cell inconsistency and high energy consumption caused by the current rough air-cooling design and proposes the optimal air-cooling design scheme of the energy storage battery box, which makes the structure of battery module more reasonable and the temperature distribution between the batteries more uniform. It has a certain guiding significance for energy saving, consumption reduction, and stable operation of energy storage systems.

LEO Small-Scale Experimental Regional Navigation Constellation Design and Optimization

In order to demonstrate the key functionalities of large-scale LEO navigation constellations, this paper investigates the small-scale LEO experimental constellation design problem. The major requirements include achieving quadruple coverage of specific ground target areas. The regional navigation constellation consists of four satellites distributed on two orbit planes. Considering the sustainable regional navigation, it is expected that the orbits of the satellites are regressional such that it takes little effort for the constellation to cover the designated region. In this way, the structure of the optimization problem is set up, which is constrained by the quadruple coverage and accuracy requirements. It takes the maximum task time as the objective function. The differential evolution algorithm (DE) is utilized to solve the optimization problem. The optimal regional navigation constellation design scheme satisfying the constraints is obtained. The simulation results show that the regional navigation constellation designed by this method can meet the predetermined requirements.

Joint Beamforming and PD Orientation Design for Mobile Visible Light Communications

In this paper, we propose joint beamforming and photo-detector (PD) orientation (BO) optimization schemes for mobile visible light communication (VLC) with the orientation adjustable receiver (OAR). Since VLC is sensitive to line-of-sight propagation, we first establish the OAR model and the human body blockage model for mobile VLC user equipment (UE). To guarantee the quality of service (QoS) of mobile VLC, we jointly optimize BO with minimal UE the power consumption for both fixed and random UE orientation cases. For the fixed UE orientation case, since the transmit beamforming and the PD orientation are mutually coupled, the joint BO optimization problem is nonconvex and intractable. To address this challenge, we propose an alternating optimization algorithm to obtain the transmit beamforming and the PD orientation. For the random UE orientation case, we further propose a robust alternating BO optimization algorithm to ensure the worst-case QoS requirement of the mobile UE. Finally, the performance of joint BO optimization design schemes are evaluated for mobile VLC through numerical experiments.

Analysis of Dynamic Characteristics of Attached High Rise Risers

The exhaust chimney of third-generation nuclear power units is a typical attached high-rise riser structure. In this paper, the simplified mechanical model and dynamic model of China’s third-generation nuclear power Hualong-1 VNA system, including multiple nonlinear factors, are established for the first time. The DTM (differential transformation method) was first applied to solve the natural vibration characteristics of a multi-point constrained variable cross-section riser structure, and the effects of variable cross-section, variable mass, variable axial force, and different elastic constraint parameters on the natural vibration characteristics of the system were studied. The dynamic behavior of the VNA system under the combined action of internal flow velocity, vortex excitation, and foundation excitation was studied. The results show that the outer diameter function of the VNA system pipeline should be designed as a quadratic function or a near quadratic multi-segment constant value function. The “limiting” effect of constraining large stiffness can force low-order vibration modes with high constraint stiffness to jump to high-order vibration modes with low constraint stiffness. The elastic constraint arrangement scheme with near center symmetry can make the system vibration mode present a half stable and half-curved form. A new optimization design scheme has been proposed regarding the layout and stiffness parameters of the VNA system guide bracket. This can enable the VNA system pipeline to avoid severe oscillations near the response extreme values caused by multiple frequency excitations of seismic loads under design and accident conditions and ensure the service life of the equipment.

A multi-subgroup decision-making method for design selection based on subjective reports and objective physiological index data

Selecting an optimal product design scheme requires considering multiple criteria and engaging the wisdom of crowds. However, existing studies regarding design selection rarely considered the participation of group wisdom, and few studies considered subjective reports and physiological index data comprehensively for evaluation. This study developed a multi-subgroup decision-making method based on the participation of designers, experts, and customers. Multi-modal aggregation strategies are applied to aggregate subjective evaluations of both individuals and groups represented in probabilistic linguistic term sets (PLTSs), objective eye movement, and Electroencephalogram feature data. Specifically, a probabilistic linguistic information aggregation operator based on the Choquet integral is proposed to aggregate the values of subjective criteria with correlations, and the double normalization-based multi-aggregation method is then applied to aggregate objective criteria values, which can avoid information loss in the normalization and aggregation. Finally, the Choquet integral-based Borda operator is developed to integrate the evaluation results of multiple subgroups. An example of evaluating intelligent shared vehicle design schemes is presented to validate the proposed method.

Polarization Optical Design of 8-meter Chinese Giant Solar Telescope

Instrumental polarization is a vital factor for the accurate measurements of the solar magnetic field. It is necessary to optimize the optical design of the large solar telescope to obtain high accuracy solar magnetic field information. In this paper, an optimal design scheme based on four-mirror polarization compensation optics for the 8-meter giant solar telescope is presented. The polarization effect of pupil and field of view are analyzed by the polarization ray tracing programming, the telescope motion and wavelength properties of the field-effect are investigated detailedly. The result shows that, in the near infrared waveband which includes the magnetic sensitive spectral lines of He I 1.083 μm and Fe I 1.565 μm, the polarization-free field size is 0.91′, and the polarization-free field size in the visible band is 0.5′, in which the instrumental polarization of telescope is smaller than 2×10−4.

Two-Stage Robust Design of Resilient Active Distribution Networks Considering Random Tie Line Outages and Outage Propagation

This paper proposes a two-stage method for the robust design of resilient active distribution networks (ADNs) against high-impact and low-probability (HILP) events. The line hardening and the deployment of remote-controlled switches (RCSs) are considered as two powerful measures for resilience enhancement. Especially, the hardening of tie lines and the deployment of bilateral tie switches are emphasized as part of the resilient design. A novel progressive detection mechanism (PDM) is devised to estimate the potential propagation of outages and identify surviving nodes outside of the minimum outage area after intentional islanding. The proposed PDM method considers potential RCS locations among regular lines and tie lines on outage to calculate the global optimal design scheme. The two-stage robust design model is formulated as a mixed-integer linear programming (MILP). The nested column-and-constraint generation (nested C&CG) algorithm is customized to solve the proposed model. Numerical results on a modified IEEE 33-node distribution system demonstrate the effectiveness and the superiority of the proposed resilience enhancement method.

OPTIMIZATION OF CALCULATIONS OF BUILDING STRUCTURES

Building structures are very diverse in their shapes, sizes, loading conditions, etc. Their durability depends on many factors, including how accurately the design scheme reflects the actual conditions of its operation. Because no matter how precise and complex calculation methods are used, if an incorrect calculation scheme is calculated, then the results of such calculations will not reflect the true picture. Therefore, the problem of optimization of design schemes is of great scientific and practical importance. Optimization parameters depend on specific conditions. One of the existing approaches for finding optimal solutions is based on mathematical modeling, when the model is an analytical dependence of the objective function on dependent (controlled) variables, the numerical values and range of which are set based on the actual operating conditions of this structure. The compilation of such models and the performance of appropriate calculations require a deep understanding of the essence of the phenomenon and knowledge of the mathematical apparatus. Of the existing methods, the most common and developed is linear programming, when the model is a linear function and the variables in the constraint system are also linear. The idea of the method is technically implemented in the add-in "Search for a solution" for Microsoft Excel. With its help, you can find the optimal (maximum or minimum) numerical value of the objective function contained in one cell, taking into account restrictions on the values of dependent variables in other cells. Most often, this superstructure is used in solving optimization problems of the economy (simplex method, transport problem, etc.). In the public domain, there are very few results of using this approach in the calculations of building structures at the initial design stage. In the proposed work, an attempt was made to use this add-on in the problem of optimizing the geometric dimensions of a structure, when the numerical value of the bending moment in a particular section was chosen as the optimization criterion. It is appropriate to solve such a problem at the stage of drawing up the design scheme of the structure. Keywords: calculation scheme, line of influence, search for solutions

Dance Video Motion Recognition Based on Computer Vision and Image Processing

ABSTRACT In recent years, motion recognition has become a hot research topic in the field of computer vision and has great research worth. Scholars and research institutions at home and abroad have made a lot of research and achieved good results. However, the research results of applying motion recognition technology to dance video are relatively few, mainly because the complexity of human motion in dance video is relatively high. In article, an optimized design scheme for motion recognition research of dance video based on computer vision and image processing is proposed. The collected dance video is preprocessed, including grayscale, background subtraction and filter denoising, so as to extract the character features in the video image. Then, the method of self-organizing mapping neural network (SOM) in computer vision is used to realize the recognition of dance movements. Finally, the simulation test and analysis are carried out. The simulation results show that the proposed arithmetic has a certain accuracy, which is 9.34% higher than the traditional arithmetic. The research of motion recognition method based on dance video will also play a certain reference role for the research of human motion recognition in a large number of real and complex environments, and enrich the application field of motion recognition technology.

Stress Characteristics and Structural Optimization of Spacecraft Multilayer Insulation Components

Multilayer insulation (MLI) components are important parts of spacecraft, in which thin films are the core elements. The film thicknesses are generally small, between 10 and 30 μm, to reduce the weight of the spacecraft. During the launch of a spacecraft, there is a rapid drop in the internal pressure, which causes the internal gas to flow out rapidly through the component. The resulting fluid force may cause film damage and failure, thereby directly affecting the normal operation of the spacecraft. Therefore, the mechanical characteristics of the thin films under rapid decompression conditions were investigated during this study. Considering the effects of the flow field stress distributions on the films during the rapid decompression, a fluid–structure interaction (FSI) model for a component was first constructed. The results show that the stress is largest in the outlet film, which is the part of the overall structure most vulnerable to failure. Furthermore, the effects of the structural parameters of the component on the stresses in the different film layers were analyzed using the orthogonal experimental method. The results show that the film thickness had the largest influence, followed by the film hole diameter, the number of component layers, and finally the staggered hole distance. Finally, a structurally optimized design scheme for the component is proposed based on a parameter range analysis with respect to the maximum film stress. After optimization, the maximum stress of the thin film decreased by 97.6%. This research has practical engineering value for the structural design and optimization of MLI components.

An Intelligent Redesign Method for Used Products Based on Digital Twin

Remanufacturing used products is an important technological approach in sustainable development and circular economy. Meanwhile, redesign is the key component of remanufacturing, as it can innovate the function and structure of used products. However, due to the uncertain quality, variety, and small batches of the returned used products for remanufacturing, it is difficult to generate a sound redesign scheme to satisfy the customer demand quickly and dynamically. In addition, it is unpredictable whether the redesign scheme is suitable for the remanufacturing processes, which may lead to additional remanufacturing costs. In order to improve the efficiency of design and obtain the optimal design scheme, it is necessary to use intelligent technology to quickly generate and optimize the redesign scheme. To address this, an intelligent redesign method for used products based on the digital twin is proposed in this paper. Digital twin (DT) technology can connect the physical world with the virtual world and use the virtual model to simulate the redesign process, which is conducive to the dynamic adjustment and optimization of the redesign scheme. Firstly, the redesign process framework is constructed based on the axiomatic design (AD) method, and the redesign features of the used products are analyzed to determine the redesign problems. Then, based on the connotation of a digital twin, an intelligent redesign framework is constructed, which provides detailed guidance for building the digital-twin-driven redesign system. Henceforth, the application of the redesign process based on a digital twin is discussed, a technical approach of the digital-twin-driven redesign is proposed, and data processing methods, such as data cleaning, data integration, and data analysis, are used to realize the redesign scheme decision. Finally, the feasibility of this method is verified by the redesign of a used clutch.

Design and optimization of a type-C tank for liquid hydrogen marine transport

As one of the most promising renewable energy sources, hydrogen has the excellent environmental benefit of producing zero emissions. A key technical challenge in using hydrogen across sectors is placed on its storage technology. The storage temperature of liquid hydrogen (20 K, or −253 °C) is close to absolute zero so the storage materials and the insulation layers are subjected to extremely stringent requirements against the cryogenic behaviour of the medium. In this context, this research proposed to design a large liquid hydrogen type-C tank with AISI (American Iron and Steel Institution) type 316 L stainless steel as the metal barrier, using Vapor-Cooled Shield (VCS) and Rigid Polyurethane Foams (RPF) as the insulation layer. A parametric study on the design of the insulation layer was carried out by establishing a thermodynamic model. The effects of VCS location on heat ingress to the liquid hydrogen transport tank and insulation temperature distribution were investigated, and the optimal location of the VCS in the insulation was identified. Research outcomes finally suggest two optimal design schemes: (1) when the thickness of the insulation layer is determined, Self-evaporation Vapor-Cooled Shield (SVCS) and Forced-evaporation Vapor-Cooled Shield (FVCS) can reduce heat transfer by 47.84% and 85.86% respectively; (2) when the liquid hydrogen evaporation capacity is determined, SVCS and FVCS can reduce the thickness of the insulation layer by 50% and 67.93% respectively.