Optimal Scheme Research Articles

Optimal Space Vector-Based Hybrid PWM Scheme in Terms of Common-Mode Voltage and Line Current Ripple

Optimal Space Vector-Based Hybrid PWM Scheme in Terms of Common-Mode Voltage and Line Current Ripple

Simulation Optimization and Experimental Validation of Hydraulic Impact in Pruning Machines

Abstract This study addresses the instability caused by hydraulic shocks in fruit tree pruning machines during operation and proposes an optimization scheme that combines simulation with experimentation. We investigated the mechanisms of load shock in the hydraulic system through mathematical modeling and LS-DYNA simulation analysis. The optimal operating parameters were determined using mechanical and orthogonal analyses: a forward speed of 4 km/h, a pruning tool angle of 60°, and a saw blade rotation speed of 1200 r/min.Additionally, we employed AMESim simulation to optimize the hydraulic system of the pruning machine by designing a dual accumulator configuration to effectively suppress hydraulic shocks.We validated the optimized system through simulations and experimental tests, demonstrating significant reductions in pressure fluctuations, with cutting efficiency improved by 30% and pressure fluctuations reduced by 26.7%.This study not only presents an innovative dual accumulator design but also validates its effectiveness in pruning machines through simulations and experiments, thereby enhancing the operational efficiency and stability of agricultural machinery.

Refracturing Time Optimization Considering the Effect of Induced Stress by Pressure Depletion in the Shale Reservoir

Refracturing is an important technology for tapping remaining oil and gas areas and enhancing recovery in old oilfields. However, a complete and detailed refracturing timing optimization scheme has not yet been proposed. In this paper, based on the finite volume method and the embedded discrete fracture model, a new coupled fluid flow/geomechanics pore-elastic-fractured reservoir model is developed. The COMSOL 3.5 commercial software was used to verify the accuracy of our model, and by studying the influence of matrix permeability, initial stress difference, cluster spacing, and fracture half-length on the orientation of maximum horizontal stress, a timing optimization method for refracturing is proposed. The results of this paper show that the principle of optimizing the refracturing timing is to avoid the time window where the percentage of Type I (Type I indicates that stress inversion has occurred, 0∘≤α≤20∘; Type II indicates that the turning degree is strong, 20∘<α≤70∘; and Type III indicates less stress reorientation, 70∘<α≤90∘) stress reorientation area is relatively large, so that the fractures can extend perpendicular to the horizontal wellbore. At the same time, the simulation results show that with the increase in production time, the percentage of Type I and Type II increases first and then decreases, while the percentage of Type III decreases first and then increases. When the reservoir permeability, stress difference, and cluster spacing are larger, the two types of refracturing measures can be implemented earlier. But, with the increase in fracture half-length, the timing of refracturing Method I is earlier, and the timing of refracturing Method II is later. The research results of this paper are of great significance to the perfection of the refracturing theory and the optimization of refracturing design.

Optimal Configuration Model for Large Capacity Synchronous Condenser Considering Transient Voltage Stability in Multiple UHV DC Receiving End Grids

In a multi-fed DC environment, the UHV DC recipient grid faces significant challenges related to DC phase shift failure and voltage instability due to the high AC/DC coupling strength and low system inertia level. While the new large-capacity synchronous condensers (SCs) can provide effective transient reactive power support, the associated investment and operation costs are high. Therefore, it is valuable to investigate the optimization of SC configuration at key nodes in the recipient grid in a scientific and rational manner. This study begins by qualitatively and quantitatively analyzing the dynamic characteristics of DC reactive power and induction motors under AC faults. The sub-transient and transient reactive power output model is established to describe the SC output characteristics, elucidating the coupling relationship between the SC’s reactive power output and the DC reactive power demand at different time scales. Subsequently, a critical stabilized voltage index for dynamic loads is defined, and the SC’s reactive power compensation target is quantitatively calculated across different time scales, revealing the impact of transient changes in DC reactive power on the transient voltage stability of the multi-fed DC environment with dynamic load integration. Finally, an optimal configuration model for the large-capacity SC is proposed under the critical stability constraint of dynamic loads to maximize the SC’s reactive power support capability at the lowest economic cost. The proposed model is validated in a multi-fed DC area, demonstrating that the optimal configuration scheme effectively addresses issues related to DC phase shift failures and voltage instability resulting from AC bus voltage drops.

Ship Type Selection and Cost Optimization of Marine Container Ships Based on Genetic Algorithm

In the context of the deep-sea transportation supply chain, this paper addresses the complex decision-making problem of vessel allocation and carbon emission optimization for container shipping routes. A bi-level programming model is established, with the upper level aiming to minimize the total operational cost and the lower level focusing on minimizing carbon emissions. Using an example of an operator with five different types of vessels, a genetic algorithm is employed to determine the optimal vessel allocation scheme. The results indicate that the vessel allocation scheme obtained through multiple iterations of the model effectively reduces both carbon emissions and operational costs. Under the condition that the preset labor cost increases year by year, the use of model optimization can significantly reduce the growth of total operating costs. This paper provides theoretical support and practical guidance for shipping companies aiming to optimize decision-making in order to reduce operational costs and carbon emissions.

Massive Data HBase Storage Method for Electronic Archive Management

ABSTRACTThe acceleration of the digitalization process in enterprise and university education management has generated a massive amount of electronic archive data. In order to improve the intelligence, storage quality, and efficiency of electronic records management and achieve efficient storage and fast retrieval of data storage models, this study proposes a massive data storage model based on HBase and its retrieval optimization scheme design. In addition, HDFS is introduced to construct a two‐level storage structure and optimize values to improve the scalability and load balancing of HBase, and the retrieval efficiency of the HBase storage model is improved through SL‐TCR and BF filters. The results indicated that HDFS could automatically recover data after node, network partition, and NameNode failures. The write time of HBase was 56 s, which was 132 and 246 s less than Cassandra and CockroachDB. The query latency was reduced by 23% and 32%, and the query time was reduced by 9988.51 ms, demonstrating high reliability and efficiency. The delay of BF‐SL‐TCL was 1379.28 s after 1000 searches, which was 224.78 and 212.74 s less than SL‐TCL and Blockchain Retrieval Acceleration and reduced the delay under high search times. In summary, this storage model has obvious advantages in storing massive amounts of electronic archive data and has high security and retrieval efficiency, which provides important reference for the design of storage models for future electronic archive management. The storage model designed by the research institute has obvious advantages in storing massive electronic archive data, solving the problem of lack of scalability in electronic archive management when facing massive data, and has high security and retrieval efficiency. It has important reference for the design of storage models for future electronic archive management.

Fast‐MedNeXt: Accelerating the MedNeXt Architecture to Improve Brain Tumour Segmentation Efficiency

ABSTRACTWith the rapid development of medical imaging technology, 3D image segmentation technology has gradually become a mainstream method, especially in brain tumour detection and diagnosis showing its unique advantages. The technique makes full use of 3D spatial information to locate and analyze tumours more accurately, thus playing an important role in improving diagnostic accuracy, optimising treatment planning and promoting research. However, it also suffers from significant computational expenditure and delayed processing pace. In this paper, we propose an innovative optimisation scheme to address this problem. We thoroughly investigate the MedNeXt network and propose Fast‐MedNeXt, which aims to increase the processing speed while maintaining accuracy. First, we introduce the partial convolution (PConv) technique, which replaces the deep convolutional layers in the network. This improvement effectively reduces computation and memory requirements while maintaining efficient feature extraction. Second, based on PConv, we propose PConv‐Down and PConv‐Up modules, which are applied to the up‐sampling and down‐sampling modules to further optimise the network structure and improve efficiency. To confirm the efficacy of the approach, we carried out a sequence of tests in the multimodal brain tumour segmentation challenge 2021 (BraTS2021). By comparing with the MedNeXt series network, the Fast‐MedNeXt reduced the latency by 22.1%, 20.5%, 15.8%, and 11.4% respectively, while the average accuracy also increased by 0.475% and 0.2% respectively. These significant performance improvements demonstrate the effectiveness of Fast‐MedNeXt in 3D medical image segmentation tasks and provide a new and more efficient solution for the field.

Optimal Design of Smart Antenna Arrays for Beamforming, Direction Finding, and Null Placement Using the Soft Computing Method

ABSTRACTThe urge of modern communication system is to design and development of the smart antennas with adaptive radiation characteristics. The multifold capabilities of fourth‐dimensional antenna arrays can cater that much needed adaptiveness if properly designed. Compared to the conventional arrays, the fourth‐dimensional arrays have one added advantage as the ‘Time’ of all the switched‐on antenna elements can be managed to generate the required amplitude and phase tapering without even using attenuators and phase shifters. However, one inherent limitation of fourth‐dimensional control parameter is the generation of harmonics or sidebands. This article proposes various means of radiation pattern synthesis in fourth‐dimensional linear antenna arrays with pulse shifting, pulse splitting, and a combination of both. First of all, the pulse splitting and shifting techniques are combinedly proposed by reducing the sidelobe levels and sideband levels of the beamforming antenna arrays to enhance directivities and efficiencies. Then, this mathematical proposition of the direction finding fourth‐dimensional arrays is developed. Finally, broad nulls over a specific angle of arrival region are created for jamming and interference mitigation. For all these cases, the sidelobe level and the unwanted higher‐order sideband levels are suppressed to reduce the unwanted interferences and power losses. The optimal time schemes for all the synthesized patterns are generated by proposing a chaos‐based soft computing algorithm. The radiofrequency signals at each radiating array element are processed by the optimal time schemes proposed for specific applications. The outcomes are validated and compared with other state‐of‐the‐art works of this domain to prove the competency of the proposed work. The qualitative and quantitative comparisons presented for beamforming array is aimed for a good improvement over other reported works by targeting ultralow (less than −40 dB) sidelobe and sideband levels. For direction‐finding array, the proposed idea has also targeted ultralow sidelobes for the main as well as steered beam patterns. Furthermore, the null placement over a region has been aimed to cover more area for jamming and sidelobe reduction for interference mitigation. Overall, the optimal designs proposed for these advanced applications are beneficial for cutting‐edge communication systems.

Assessment of the Choked Flow Model of RELAP5 for Application of Inverse Quantification Methods

In the framework of deterministic safety analysis, best estimate plus uncertainty methodologies can provide a more informative detailed analysis of transients than conservative approaches. However, one important step in the application of such methodologies is derivation of uncertainty of the physical models. Probability density functions of the physical model parameters are obtained by applying inverse uncertainty quantification (IUQ) methods to experimental data. The present work deals with evaluation of the experimental database and assessment of the simulation model, which are required steps prior to the application of IUQ methods. The U.S. Nuclear Regulatory Commission system code RELAP5 has been applied for simulation of three experimental databases on choked/critical flow: Sozzi-Sutherland, Super MobyDick, and Marviken Critical Flow Tests. First, the adequacy of the experimental data to the specific target domain is carried out, to then proceed to calibration of the input model parameters by combining the use of Gaussian Process metamodels and optimization schemes. The assessment of the simulation models is performed by evaluating independently accuracy, precision, and consistency through four statistical indicators, including a novel indicator to evaluate the consistency of the results. The final results indicate that the model is capable of reproducing the selected experimental database and overall average accuracy, precision, and consistency below the 10% threshold and can be used for application of IUQ methods.

Performance enhancement of magnetoactive elastomer soft robots through a coupled magnetoelastic topology optimization scheme

Abstract We have found that considering local magnetic fields, large deformations, and magnetoelastic coupling simultaneously significantly affect the resulting shape in magnetoelastic topology optimization in a uniaxial actuator case. In contrast to the work presented here, other works incorporate magnetoelastic formulations that include simplifying assumptions on the local field, and subsequent effects on the magnetization response of the material, or the absence of large deformation mechanics, or both. These assumptions were shown to produce solutions that differ substantively from cases where local fields and large deformations are addressed concurrently. Magnetoelastic topology optimization schemes are needed to optimize magnetoactive elastomer (MAE) devices. MAE devices are magnetic particle-filled polymer matrices designed for specific actuations and controlled remotely by an external magnetic field. They garner considerable research interest as an emerging technology for actuators in soft robots or in applications requiring untethered actuation. The material properties of MAEs are dependent on the volume fraction of particles in the elastomer matrix, where a high-volume fraction increases relative permeability (for soft magnetic particles) but also increases elastic modulus. For optimal actuation, a tradeoff between low stiffness and high magnetic response must be made by adjusting volume fraction and controlling material placement. Using a topology optimization scheme that considers both the magnetic and mechanical properties of the material, the shape and material composition of the device can be tuned to best achieve the desired actuation displacement. In this work, a density-based magnetoelastic multimaterial topology optimization scheme for soft magnetic material is developed in COMSOL Multiphysics. The optimization scheme uses multiphysics coupling that considers local magnetic fields and large deformations at each iteration through a Maxwell stress tensor formulation. A simulated example is then considered to demonstrate the effectiveness and necessity of a coupled optimization. The effect of considering large deformations during optimization is also investigated. It was found that a coupled topology optimization scheme with large deformations produced shapes with modes of actuation not captured by schemes with simplifying assumptions, leading to better performance at lower material cost. Considering large deformations in the coupled scheme offered significantly better performance, with an increase of 81.3% in a side-by-side performance simulation when compared to uncoupled cases.

Research on the Arrangement Scheme of Spirally Twisted Tape Inserts in a Grate Furnace

To eliminate the flow dead zone and homogenize the asymmetric flow field of a grate furnace, spirally twisted tape inserts (STTIs) with a pitch ratio of 1.5 were installed in the vertical flues of an SCL1000-13.5/450 grate boiler. The arrangement schemes found to be present inside the chosen 1000 t/d grate furnace, determined using the orthogonal experimental method, included separate installation in chamber II, separate placement in chamber III, and simultaneous arrangement in both chamber II and chamber III. The effects of row spacing H, column spacing W, and mounting angle φ were investigated by means of the practicable and feasible numerical simulation method. With a focus on the uniformity degree of the flue gas, the results showed that temperature distribution is directly correlated with the velocity field. When it comes to the uniformity of the flow field, the exclusive use of STTIs in chamber II was better than that in chamber III. Under the optimal combination scheme of STTIs in both chamber II and chamber III (scheme N323), the exhaust gas temperature reached the minimum value and the uniformity index of temperature increased to the range of 0.994~0.997. The findings in this work could provide a reference for the optimization of the flow field in a grate furnace.

Enhancing COVID-19 disease severity classification through advanced transfer learning techniques and optimal weight initialization schemes

ObjectiveMedical imaging plays a central role in medicine today by supporting diagnosis and treatment. For small medical image datasets, training from scratch is a time-consuming process and transfer learning emerges as a solution. In these cases, ImageNet weights are usually used as initial weights, after which fine-tuning is performed. We propose a methodology for COVID-19 severity classification (mild, moderate, severe, critical) in chest X-ray images based on transfer learning using DenseNet121 architecture as a base model. MethodsThe novelty of the approach mainly lies in the investigation of three different weight initialization schemes (i) ImageNet (ii) CheXNeXt (iii) DeepCOVID-XR, which are similar in a graded manner in terms of image nature, with ImageNet being the least similar, CheXNeXt similar as they were trained on different lung diseases not including COVID-19 and DeepCOVID-XR the most similar as they were obtained by training specifically on COVID-19 X-ray images. ResultsThe results show that the worst results are achieved using ImageNet as initial weights (average AUC = 0.700), followed by the better results with DeepCOVID-XR (average AUC = 0.774) while CheXNeXt performed significantly better (average AUC = 0.917). The results of weaker performing classification models were improved when the severe and critical classes were merged, to account for the similarity between these classes in the dataset (average AUC for initialization schemes were ImageNet AUC = 0.867, CheXNeXt AUC = 0.900 and DeepCOVID-XR AUC = 0.794). ConclusionThis leads to a conclusion that, in the medical domain, where image datasets are usually small and highly imbalanced, if initial weights are chosen to be in nature similar to the new dataset, achieved results are better. However, there is no need to start from weights obtained during training on the same disease, as this may cause overfitting. There are significant discrepancies between ImageNet and medical imaging datasets and the results from this paper could help in guiding future implementations of transfer learning in medical applications.

Simulation and Optimization of Transmitting Transducers for Well Logging

Piezoelectric transducers are commonly used in acoustic well logging. However, the low frequency and narrow range of the acoustic waves limit the achievable detection accuracy. In addition, the low amplitude of the waves causes useful information to be easily masked by noise during detection, which affects the accuracy of geological identification and makes it difficult to detect formations tens of meters away. This paper proposes a microporous liquid–electric transmission transducer, in which the microporous electrode structure generates a powerful shock wave through a high-energy instantaneous discharge. First, a model of the liquid–electric microporous transmitting transducer was constructed by combining simulations with numerical calculations, and its electro-acoustic characteristics were analyzed. Then, based on the survey requirements, two innovative optimization schemes for the microporous electrode structure were proposed, namely a triangular pyramid microporous electrode structure and a rectangular microporous electrode structure, and their performances were compared. The results show that the newly optimized triangular pyramid microporous electrode liquid–electric transducer generates acoustic waves with higher amplitude and a wider frequency range than conventional piezoelectric transducers and other microporous structures. It maintains high energy while achieving high frequencies, enabling detection at distances of up to hundreds of meters and the precise characterization of small geological bodies. This has significant implications for applications in marine exploration, land exploration, clean energy, and new energy fields.

Laboratory Experimental Investigation on the Structural Optimization of a Novel Coupled Energy Tunnel

Freezing damage to tunnels in cold regions has long posed a threat to the safe operation of high-speed trains and other means of transportation. Finding a reasonable and effective solution to this problem, while also considering green, low-carbon, energy-saving, and environmental protection measures, has garnered widespread attention. Herein, the concept of a novel coupled energy tunnel is proposed, which combines the technologies of an air curtain and ground source heat pump (GSHP). The aim is to effectively address the issue of freezing damage in tunnels located in cold regions, while ensuring traffic safety. First, the multifunctional experimental apparatus for testing the anti-freezing and insulation performance of a coupled energy tunnel was independently designed and developed for laboratory experiments. Second, single-factor experiments and orthogonal experiments are conducted, and the influences of five key factors (i.e., the air outlet hole diameter, air outlet hole spacing, circulating water temperature of the GSHP, wind speed at the tunnel model entrance, and airflow jet angle) on the internal temperature field of the tunnel model are discussed. Third, combined with range analysis and variance analysis, the ranking of importance for each key factor and the optimal scheme of the coupled energy tunnel are obtained as follows: wind speed at the tunnel model entrance D > circulating water temperature of GSHP C > airflow jet angle E > air outlet hole spacing B > air outlet hole diameter A, and the optimal scheme is A2B1C4D1E2, i.e., the air outlet hole diameter is 3 mm, the air outlet hole spacing is 10 mm, the circulating water temperature of GSHP is 50 °C, the wind speed at the tunnel model entrance is 1.5 m/s and the airflow jet angle is 45°. In conclusion, the research achievements presented in this paper can offer a new perspective for the structural design of tunnels in cold regions. Additionally, they contribute to the early achievement of a carbon dioxide emissions peak and carbon neutrality, and provide some valuable and scientific references for both innovators and practitioners.

Comparative Study on Artificial Fracture Modeling Schemes in Tight Reservoirs—For Enhancing the Production Efficiency of Tight Oil and Gas

In order to improve the reliability of the deployment of production schemes after artificial fracturing in tight reservoirs, it is urgent to carry out research on the description of fractures after artificial fracturing. In this study, taking the Chang 61 oil formation group in the Wangyao South area of Ordos Basin as an example, three different fracture modeling schemes are used to establish the geological model of fractured reservoirs, and the fitting ratios of the respective reservoir models are calculated by using the method of reservoir numerical simulation of the initial fitting, and the optimal fractured reservoir modeling scheme is screened in the end. The research area adopts three types of fracture prediction results based on FMI fracture interpretation data, seismic fracture prediction data, and rock mechanics artificial fracturing simulation data. On this basis, geological models of fractured reservoirs are established, respectively. The initial fitting of reservoir values of each geological model are compared, and the highest initial fitting rate of reservoir values is 88.44%, which is based on rock mechanics artificial fracturing simulation data. However, the initial fitting rate of the reservoir model was the lowest at 75.76%, which was established based on the fracture random modeling results of FMl fracture interpretation data. Under the constraints of seismic geostress prediction results and microseismic monitoring data, the simulation results of rock mechanics artificial fracturing fracture are used as the basis, on which the geological model of artificially fractured reservoirs is thus established, and this scheme can more realistically characterize the characteristics of fractured reservoirs after artificial fracturing in the study area.

Theoretical analysis of heat and mass transfer characteristics of a counter-flow packing tower with different heating modes

Mass extraction/injection and multi-stage system have been proven to be effective approaches to improve the performance of humidification and dehumidification (HDH) desalination system. However, these two optimization schemes cause that the flow ratios of water to air at different positions of humidifier or that of different humidifiers have great difference. A single heating mode is inapplicable to all flow ratios of water to air. Hence, it is necessary to reveal the relationship among mass flow ratio, heating mode and thermal efficiency of humidifier for the selection of appropriate heating mode. A theoretical model of packing tower (typical kind of humidifier) which agrees well with experimental results was established in this paper, and the average relative errors of outlet air temperature, humidity and thermal efficiency are 2.3 %, 4.9 % and 5.8 %, respectively. A comparison among the thermal efficiencies of a counter-flow packing tower with different heating modes (I: solution heated, II: air heated, III: solution-air heated) was conducted. It is found that there exist two values of mass flow ratio (FRI-II and FRII-III) at which the thermal efficiencies of air heated and solution-air heated are equal and that of solution heated and solution-air heated are equal, respectively. However, the thermal efficiency of solution heated is always higher than that of solution-air heated (FRI-III does not exist). It seems clear that there is a relationship between FR and thermal efficiency (η) as follows: FR < FRI-II, ηI > ηIII > ηII; FRI-II < FR < FRII-III, ηI > ηII > ηIII; FR > FRI-II, ηII > ηI > ηIII. Additionally, the effects of inlet parameters on the FRI-II and FRII-III are also evaluated. The results show that the maximum temperature, inlet solution concentration and ambient temperature have positive effects on FRI-II and FRII-III, but ambient relative humidity has negative effect. In the final part, the selection of the heating mode of a counter-flow packing tower is taken as example to introduce the application of FRI-II and FRII-III proposed in this paper.

Rate Optimization of Intelligent Reflecting Surface-Assisted Coal Mine Wireless Communication Systems.

This paper proposes a three-step joint rate optimization method for intelligent reflecting surface (IRS)-assisted coal mine wireless communication systems. Different from terrestrial IRS-assisted communication scenarios, in coal mines, IRSs can be installed flexibly on the tops of rectangular tunnels to address the issues of signals being blocked and interfered with by mining equipment. Therefore, it is necessary to optimize the IRS deployment position, the transmit power and IRS phase shifts to achieve the maximum effective achievable rate at user stations equipped with the proposed system. However, due to the complex channel models of coal mines, the optimization problem of IRS deployment position is non-convex. To solve this problem, two auxiliary variables along with logarithmic operations and Taylor approximation are introduced. On this basis, a three-step joint rate optimization involving the transmit power, IRS phase shifts and IRS deployment position is proposed to maximize the effective achievable rates at the user station. The simulation results show that compared with other rate optimization schemes, the effective achievable rates at the user station using the proposed joint rate optimization scheme can be improved by approximately 12.32% to 54.17% for different parameter configurations. It is also pointed out that the deployment position of the IRS can converge to the same optimal position independent of the initial deployment position. Moreover, we investigate the effects of the roughness of the tunnel walls in a coal mine on the effective achievable rates at the user station, and the simulation results indicate that the proposed three-step joint rate optimization scheme performs better in the coal mine scenario regardless of the roughness.

Optimization of Manure-Based Substrate Preparation to Reduce Nutrients Losses and Improve Quality for Growth of Agaricus bisporus

With the growing world population, food demand has also increased, resulting in increased agricultural waste and livestock manure production. Wheat straw and cow dung are rich nutrient sources and, if not utilized properly, may lead to environmental pollution. Keeping in view the cultivation of Agaricus bisporus on straw/manure-based substrate, the current study aimed to optimize the conventional manure preparation technique to reduce nutrient losses and keep the quality of manure at its best. The treatments were considered as traditional and optimized schemes for mushroom substrate preparation. The results achieved herein indicated that the nutrient losses were low in the optimum scheme. For carbon (C), the loss was 43.55% at the substrate stage in the traditional scheme and reduced to 37.75% in the optimum scheme. In the case of nitrogen (N), the loss was 22.01% in the traditional scheme and was lower (18.49%) in the optimum scheme. The nutrient concentration in Agaricus bisporus was higher with the optimum scheme compared with the traditional scheme. It was 1.74% for C, 7.17% for N, 3.58% for phosphorus (P), and 4.92% for potassium (K). The optimum scheme also improved the Agaricus bisporus yield per unit area (84.55%) and the total yield (28.92%). The net income of the optimum scheme was 102.95% higher compared to the traditional scheme. The economic analysis also revealed that the benefit–cost ratio of the optimum scheme was high (48.86%) compared with the traditional scheme. This study concludes that the use of the optimum scheme can better utilize the wheat straw and cow manure waste for substrate preparation and reducing nutrient losses. In addition, the final mushroom residue can also be used as a leftover substrate for further utilization.

Optimization of indoor thermal environment for high-altitude sentry buildings with attached ventilation based on proper orthogonal decomposition

The low-oxygen and severe cold climate characteristics of high-altitude regions significantly impact individuals' physiological health and thermal comfort inside buildings, especially for sentry buildings where the enclosure is fully exposed to the outdoors. This study aimed to optimize the indoor environment for high-altitude sentry buildings with attached ventilation. Firstly, the optimal location of exhaust outlets and oxygen sources in the heating mode of high-altitude sentry buildings was studied, and it showed high performance in terms of thermal comfort and energy efficiency. Additionally, the POD method and interpolation methods were applied to expand the sample dataset and identify the optimal combination of attached ventilation parameters and oxygen supply concentration, creating a comfortable, oxygen-enriched environment within the sentry buildings while also considering energy efficiency. The results indicate that when the optimization objective is weighted towards thermal comfort, the percentage of dissatisfied (PD) and the draught rate (DR) values under the optimal scheme are reduced by 82 % and 46.6 %, respectively, compared to previous studies. However, when the emphasis is on energy efficiency in environmental optimization, the air supply energy under the optimal scheme has a 64.4 % reduction compared to previous research results. When considering both optimization objectives simultaneously, the PD and DR values under the optimal scheme are reduced by 35.9 % and 96.9 %, respectively, compared to previous research results. These results demonstrate significant improvements in both thermal comfort and energy efficiency relative to our previous study.

Overall plan optimization of BWB UAV based on comprehensive evaluation

Based on the shape and performance characteristics of the wing-body fusion layout UAV, a multidisciplinary comprehensive analysis model, comprehensive evaluation model and optimization model suitable for the overall scheme of the UAV in the conceptual design stage are established, and the corresponding tools are developed. The geometric, weight, aerodynamic and stealth characteristics of the overall scheme of the wing-body fusion layout UAV are analyzed by combining numerical analysis and engineering methods. The improved TOPSIS method is used to establish a comprehensive evaluation model from the perspective of the loading capacity, economy and adaptability of the UAV. The rationality of the analysis model is verified by taking multiple UAV schemes as examples. Using the parallel subset simulation optimization algorithm, the traditional multi-objective optimization is completed with the maximum cruise lift-to-drag ratio and the minimum forward RCS as the goal, and the scheme optimization based on comprehensive evaluation is completed with the strongest competitiveness as the goal. Based on all the schemes generated by the multi-objective optimization process, the parameter correlation analysis is completed, and the influence of the span, sweep angle and twist angle on the aerodynamic and stealth characteristics is verified. The RCS of the final multi-objective optimization scheme is reduced 41.6%, and the cruise lift-to-drag ratio is improved 3.5% ; the competitiveness score of the comprehensive evaluation optimization scheme is improved 44.0%.