Comprehensive Performance Optimization Research Articles

Orchestrating scheduling, grouping and parallelism to enhance the performance of distributed stream computing system

In a big data stream computing environment, the arrival rate of data streams usually fluctuates over time, posing a great challenge to the elasticity of system. The performance of stream computing system is crucial, especially when dealing with unbounded and fluctuating data streams. Most prior studies have primarily focused on one or two aspects to enable elasticity, often lacking prompt and comprehensive performance optimization. This limitation could lead to a tuning bottleneck, preventing the system’s performance from consistently reaching its optimal state. Additionally, many stream computing systems are not intelligently adaptive in real time due to the challenges of manual parameter reconfiguration for fluctuating streams. To better address these issues, we propose a framework named Sgp-Stream, which orchestrates scheduling, grouping and parallelism (Sgp). To enhance the system performance. We conduct the following research: (1) Running experiments to evaluate the impact of different factors such as scheduling, grouping and parallelism on system performance. Results show that factors at a single level usually have an upper limit on tuning system performance, and better overall performance can be achieved by coordinating multi-level factors. (2) Establishing quantitative models for stream application that consider computational cost and communication cost, multi-dimensional featured data stream, data center resources, and latency & throughput performance. (3) Demonstrating the effectiveness of the proposed runtime-aware data stream grouping based on smooth weighted polling, elastic adaptive scheduling based on Linear Deterministic Greedy and elastic scaling strategy based on Gradient Descent in Sgp-Stream, for continuous performance optimization.(4) Evaluating the application latency, throughput and resource utilization objectives using a real-world elastic stream computing system and twitter data set. Experimental results show that, compared to existing state-of-the-art works, the proposed Sgp-Stream outperforms them by reducing latency by 26%–48%, improving throughput by 14%–20%, and increasing resource utilization rate by 15%–21%, especially under increasing data stream input rates.

Microstructure evolution of V-containing low carbon ultra-fine bainitic steel during medium-temperature tempering and strengthening-toughening mechanism

In the present study, the microstructure evolution and the corresponding mechanical properties of V-containing low carbon ultra-fine bainitic steel during tempering were studied. The results show that during the initial stages of tempering, part of retained austenite in V-containing ultra-fine bainite steel transforms into bainite. The stability of the retained austenite improves when the tempering period is increased to 5 h. Simultaneously, nano-sized VC precipitates are precipitated in the microstructure. On the one hand, these phases can give full play to the transformation-induced plasticity (TRIP) effect by modulating the carbon content of the retained austenite. On the other hand, they can also reduce the lattice distortion in the matrix and combine it with the lower dislocation density, thereby improving the plasticity of the specimen. At the same time, the fine precipitated phase can also effectively improve the toughness of the cleavage crack region in the transition zone, preventing the micro-cracks from generating at the interface of the precipitated phase and then extending to the adjacent matrix to cause fracture, so that the uniform elongation, total elongation, impact toughness at room temperature and impact toughness at low temperature of the 5 h specimen are as high as 8.8 ± 0.2 %、16.2 ± 0.7 %、113 ± 4 J/cm2 and 76 ± 2 J/cm2, respectively. Furthermore, the primary contribution of the strengthening mechanism in the microstructure has shifted from fine grain strengthening and dislocation strengthening to precipitation strengthening, and part of the retained austenite undergoes a martensitic transformation during cooling, resulting in the highest yield strength of 1086 MPa for the 5 h specimen. The tensile strength is effectively maintained at 1402 MPa by increasing the tempering period, which has good tempering resistance, to achieve the comprehensive performance optimization of bainitic steel.

Three-stage model predictive control for modular multilevel converters with comprehensive performance optimization

Three-stage model predictive control for modular multilevel converters with comprehensive performance optimization

Thermodynamic and emission characteristics of a hydrogen-enriched natural gas-fired boiler integrated with external flue gas recirculation and waste heat recovery

Hydrogen-enriched natural gas (HENG) is a low-carbon fuel and its utilization in combustion devices has been under extensive discussion recently as it is a promising way to reduce the CO2 emission during combustion. The applicability of HENG in the existing natural gas-fired combustion equipment in terms of its efficiency and emissions attracts increasing attention, especially for industrial and domestic small-scale boilers. In this study, the thermal efficiency and pollutant emissions of a 4.2 MWth HENG-fired boiler integrated with external flue gas recirculation (FGR) were respectively evaluated based on the thermodynamic and heat transfer models and the Chemical Reaction Network model. Results suggested that NOx emission rose by ∼19% as the hydrogen volumetric fraction in the fuel increased from 0 to 0.4 at a constant excess air ratio and FGR rate. To suppress the NOx rise, the FGR rate was tuned higher while the system thermal efficiency decreased subsequently. To further improve the overall system thermal efficiency, a cascade flue gas waste heat recovery strategy including sensible heat recovery using an external economizer and latent heat recovery using dual-spray heat exchangers was proposed. The thermodynamic analysis demonstrated that the external economizer improved the overall system thermal efficiency by 0.4% - 0.7% and the dual-spray heat exchangers promoted the overall system thermal efficiency by over 5%. Thus, a comprehensive performance optimization strategy was developed for HENG-fired boilers in terms of their overall system thermal efficiency promotion, NOx emission control, and CO2 emission reduction.

Incremental accelerated gradient descent and adaptive fine-tuning heuristic performance optimization for robotic motion planning

Robot comprehensive performance optimization is a high dimensional non-convex problem, which is of great significance in the practice of robotic intelligent manufacturing. Existing methods still face many challenges in performance evaluation, local optima, and planning efficiency. In this paper, a novel method based on accelerated gradient descent and directed-mutagenesis genetic algorithm (AGD-DGA) is proposed for efficient robotic motion planning and comprehensive performance optimization. Firstly, the time, energy consumption, and impact (T-E-I) are taken as the optimization objectives. In particular, the power loss sub-model is constructed, which is rarely considered in the previous research on motion optimization, and it is combined with the driving power sub-model to improve the evaluation accuracy. Next, a novel directed-mutagenesis genetic algorithm (DGA) is proposed to address the local optima problem. Compared with existing methods based on random sampling, the DGA further improves the success rate and efficiency by updating the probability model based on the adaptive Gaussian process. Moreover, a hierarchical weight updating mechanism is established to overcome the impact of additional performance indicators on the success rate of collision-free path planning. To improve planning efficiency, an incremental optimization mechanism and an adaptive fine-tuning strategy for population size are proposed to reduce unnecessary sampling, evaluation, and sorting. The simulation and experimental results in different scenarios demonstrate that the proposed AGD-DGA achieves better results than most of the mainstream algorithms in terms of optimization efficiency, success rate, and motion performance. In addition, it is also verified that the modified energy consumption model can achieve an average evaluation accuracy of more than 90% while maintaining the calculation efficiency.

Advancements and Applications of Rim-Driven Fans in Aerial Vehicles: A Comprehensive Review

As the aviation industry seeks sustainable propulsion solutions, innovative technologies have emerged, among which rim-driven fan (RDF) systems hold notable promise. This comprehensive review paper deeply investigates RDF technology, uncovering its principles, benefits, and transformative potential for aviation propulsion. Amid escalating concerns about greenhouse gas emissions, the aviation sector’s shift towards electric propulsion has gained impetus. RDF technology has emerged as a beacon of optimism, heralding the prospect of energy-efficient and eco-conscious air travel. Navigating the slower development pace of RDF technology for aerospace applications, this paper draws insights from analogous marine technologies and relevant literature. Merging these realms, this paper meticulously examines RDF systems, spotlighting their unique attributes, with particular emphasis on the rim-driven configuration and its fundamental design principles. This review delves into the progressive strides accomplished in RDF’s evolution, encompassing the spectrum from evolving electric motor variants to intricate design considerations, strategic noise and vibration management, innovative control methodologies, advancements in bearing technology, and the strategic integration of finite element analysis (FEA) and computational fluid dynamics (CFD) for comprehensive performance optimization. In the context of aviation’s electrification journey, the exploration of RDF technology marks a pivotal inflection point. This paper concludes by succinctly encapsulating pivotal insights, accentuating RDF technology’s central role in reshaping aviation’s propulsion paradigm. As the aviation sector charts a course towards sustainable progress, the lessons gleaned from RDF technology are poised to chart the trajectory of aviation’s environmental transformation.

Synergistic influence of carbon nanotube-graphene oxide hybrid and nanosized interfacial TiC on the mechanical performance of Cu matrix composites

Reinforcement architecture and interfacial structure are two key factors affecting the performance of composites. Herein we attempted to achieve a comprehensive improvement of mechanical properties of carbon nanomaterials (CNMs) reinforced Cu matrix composites by means of reinforcement structure construction and interface structure optimization. Graphene oxide (GO) and acid-treated carbon nanotubes (AT-CNTs) were self-assembled into a GO-CNT hybrid structure through an ultrasonic mixing method, and then used as reinforcement of Cu matrix composite through the powder metallurgy method. The strengthening efficiency of GO-CNT hybrid was significantly higher than that of individual CNTs or GO, which could be attributed to the stable interconnected architecture of GO-CNT hybrid formed through sp3 hybridized C–C bonds and the larger interfacial area between them and Cu matrix. In addition, aiming at the issue of poor interfacial adhesion between the GO-CNT hybrid and Cu matrix, TiC nanoparticles were introduced onto the surface of GO-CNT hybrid through a pressureless spark plasma sintering strategy. The TiC nanoparticles can improve the interfacial wettability and optimize the interfacial bonding state. TEM results confirmed a semi-coherent interfacial lattice matching relationship between TiC nanoparticles and Cu matrix, which was conducive to forming robust interfacial bonding. Through the construction of hybrid reinforcement and the introduction of nanosized interfacial TiC, the GO-CNT hybrid reinforced Cu matrix composite has obtained ultra-high strengthening efficiency, and exhibited satisfied combination of strength and ductility. This study can provide a referential strategy for the comprehensive performance optimization of CNMs reinforced metal matrix composites.

Strengthening Mechanisms and Thermal Models of Chemically Incompatible Metals (Mo/W–Cu): A Review

Molybdenum/tungsten–copper matrix composites are widely used in electronic engineering, aerospace, and other fields because of their excellent properties such as high hardness, high mechanical strength, low electrical and thermal conductivity, adjustable thermal expansion coefficient, and good high‐temperature stability. The densification, mechanical properties, and thermal properties are attributed to additive alloying elements, grain size and structure, and sintering parameters. Nevertheless, there are still some problems with densifying the composites due to the chemical incompatibility of molybdenum/tungsten and copper, and therefore the densification and strengthening mechanisms are reviewed to further improve densification and properties. Currently, the factors affecting thermal performance are scattered. Herein, the factors affecting the thermal conductivity of molybdenum/tungsten–copper matrix composites are reviewed, which provides a reference for the comprehensive performance optimization of molybdenum/tungsten–copper matrix composites. The future structure and simulation of molybdenum/tungsten–copper composites are also prospected. It provides a new way to improve the properties and structure of chemically incompatible metal composites.

Quantitative Weight and Two-Particle Search Algorithm to Optimize Aero-Stealth Performance of a Backward Inclined Vertical Tail

To study the influence of the tilt-back design of a vertical tail on its aerodynamic stealth characteristics, an optimization method based on a quantitative weight coefficient and a two-particle search algorithm is presented. When the aerodynamic performance of the vertical tail is optimized separately, the reduction in the drag index is obvious, and the optimal solution appears at the boundary of the backward-tilt range. The optimal solution of separate stealth optimization is different from that of separate aerodynamic optimization within the given range of tilt back. The two-particle search algorithm can provide an optimal solution for comprehensive performance optimization under different weight coefficient distributions, where the fitness index, aerodynamic index, and radar cross-section index are all significantly reduced. The presented optimization method is effective for optimizing the aerodynamic stealth performance of the vertical tail.

Research on Comprehensive Performance Optimization Method of Explosives and Propellants Oriented to the Whole Process

Explosives and propellants are common basic energy for weapons and equipment to achieve delivery, damage, and control, and are an important manifestation of national defense power. However, due to the wide variety of products and complex performance, the traditional serial design optimization mode can no longer meet the requirements of product diversification and rapid development. In this paper, the design process of explosives is deeply studied, and a method for optimizing the comprehensive performance of explosives and propellants oriented to the whole process is proposed. The method uses a comprehensive performance optimization engine to numerically model different design links in a unified parameter space, connects different links horizontally, and adopts a multi-objective optimization algorithm to comprehensively consider the optimization objectives of different links, realizing the automatic execution of the optimization process according to the design process. In order to verify the effectiveness of the method, this paper optimizes the formula of explosives and propellants based on two different types of explosives, gun propellant and rocket propellant. Experimental results show that this method improves the design efficiency and improves product quality under the premise of ensuring safety and manufacturability.

Hourly stepwise forecasting for solar irradiance using integrated hybrid models CNN-LSTM-MLP combined with error correction and VMD

Accurate and reliable solar irradiance forecasting is critical for distribution planning and modern smart grid management and dispatch. However, due to the time series of solar irradiance with the nonlinearity and nonstationarity, some researches up to now are still unsatisfactory in terms of prediction accuracy and model generalization ability. Therefore, to improve the comprehensive performance of the model, a novel forecasting framework of hourly stepwise forecasting for solar irradiance using integrated hybrid models CNN-LSTM-MLP combined with error correction and variational mode decomposition (VMD) was proposed. In this paper, three different datasets were pre-processed and then the step-by-step predictions of seven different methods were completed based on the proposed procedures. Finally, comprehensive analysis results of the model indicated that the prediction scheme proposed in this paper made full use of, step-by-step prediction, VMD method, integrated hybrid model, and error correction four major advantages greatly improved the anti-interference ability of the model, so that the average performance metrics RMSE, nRMSE, MAE, and R2 of the three datasets reach to 12.53 W/m2, 6.04 %, 7.65 W/m2, and 99.79 %, respectively. Moreover, the optimal promoting percentages of the R2(PR2)indicator compared to the persistence model (Per) is by 20.17 %. It is found that the model is superior to a large number of traditional alternative approaches in terms of accuracy and robustness, which may provide a reference for comprehensive performance optimization of the model in the future.

Multi‐Objective Optimization for the Cross Brace of a Computer Numerical Control Gantry Machine Tool Based on Intelligent Algorithms

A multi‐objective optimization design method for the cross‐brace structure of a computer numerical control gantry machine tool is proposed to improve mechanical performance. Dynamic and static performance indexes of the cross brace are analyzed. On basis of sensitivity analysis, size parameters which have great influence on mass and dynamic and static performance indexes of the cross brace are selected as design variables for optimization. Objective values under design variables are obtained by orthogonal experimental method, and an objective function is fitted by response surface method. After verifying the fitting effect of the objective function, entropy weight method is used to calculate weight coefficient of each optimization objective, and a comprehensive performance optimization model of the cross brace is built. Accelerated particle swarm optimization (APSO) intelligent algorithm is used to solve the comprehensive performance optimization model. Comparison results before and after the optimization show that the mass of optimized cross brace is reduced by 8.377%, the maximum stress is reduced by 13.252%, and the first‐order natural frequency is increased by 2.183%. The proposed optimization method provides a new idea to improve the dynamic and static performance of the cross brace while reducing its mass.

Pseudo-optimal discharge pressure analysis of transcritical CO2 electric vehicle heat pumps due to temperature glide

• A pseudo-optimal discharge pressure for electric vehicle heat pumps was proposed. • The principle of pseudo-optimal discharge pressure was explained. • Pseudo-optimal discharge pressure exists in subcritical and transcritical states. • The effects of conditions on pseudo-optimal discharge pressures were revealed. Performance improvement of electric vehicle heat pumps can enhance thermal comfort and reduce the power consumption of electric vehicles, hence stimulating their development. In this paper, the cyclic characteristics of an electric vehicle heat pump were studied under different operating modes and working conditions. Different from the optimal discharge pressure of conventional CO 2 systems which was determined by the variation gradient characteristics of the transcritical isotherm, the discharge pressure of electric vehicle heat pumps at the peak COP value was defined as a pseudo-optimal discharge pressure and was determined by the obvious temperature glide at the outlet of the gas cooler. This pseudo-optimal discharge pressure existed at both transcritical and subcritical states. The difference in the pseudo-optimal discharge pressure between the subcritical or transcritical states was first evaluated. Then an in-depth analysis of the influence of key parameters on the pseudo-optimal discharge pressure was studied to develop an accurate prediction method since the traditional prediction methods were not applicable. The results showed that pseudo-optimal discharge pressure increased with the ambient temperature, inlet air temperature, and supply air temperature. This study provides valuable information for the comprehensive performance optimization of an electric vehicle thermal management system.

A new comprehensive performance optimization approach for Earth-contact mechanism based on terrain-adaptability task

AbstractEarth-contact mechanism (ECM), a type of mechanism to keep the system in contact with the earth and to move with the terrain changes. This paper uses the virtual equivalent parallel mechanism (VEPM) to convert the terrain data into the kinematical variables of the moving platform in the VEPM, and further analyzes the performance of the VEPM at each terrain point. Then, the comprehensive performance of the VEPM is chosen as the optimization goal, and a task-oriented dimensional optimization approach combined with the particle swarm algorithm and the neural network algorithm is proposed. This paper conducted a comparative experiment to verify the superiority of the new approach in optimizing the ECM’s comprehensive performance, whose performance analysis also can be applied into the layout design of the ECM. This paper proposed an analysis method to construct the ECM’s performance map based on the digital terrain map, which helps the control system and operator to make the optimal control decision.

Investigation on the Separation Performance and Multiparameter Optimization of Decanter Centrifuges

Decanter centrifuges are widely used for solid–liquid separation. Although parameter analysis for decanter centrifuges was performed by numerical simulation in previous studies, some structural parameters are rarely mentioned and investigated. At the same time, the results obtained by the single-parameter analysis in previous studies are difficult to truly realize the comprehensive performance optimization of decanter centrifuges. In this paper, the influences of the window structure and bowl–conveyor gap on the separation performance are systematically analyzed with the employment of a numerical computation method. The results show that the increase in the window angle and window height will accelerate the flow of the upper layer, while the increase in the bowl–conveyor gap may make particles flow through it directly and further form a solid retention zone. Both of the structural changes will lead to deterioration of the separation performance. On the basis of numerical simulation analysis, a genetic algorithm-based method for multiparameter optimization is proposed in this paper. Parameter optimization shows that bowl speed and feed flow rate have the most significant effects on the separation performance and power consumption. Compared with the minimal specific power in the first generation, the optimized specific power is reduced by 15.7%, and the cake solid content merely decreases by 0.044%.

Towards fast sensing along ultralong BOTDA: flatness enhancement by utilizing injection-locked dual-bandwidth probe wave.

Brillouin optical time-domain analysis (BOTDA) using distributed Brillouin amplification (DBA) only requires a milliwatt-level pump to achieve a sensing range beyond 100 km, which provides a powerful tool for temperature/strain sensing. However, similar to the majority of other long-range BOTDAs, the state-of-the-art reports require > 1000 times average, severely restricting the sensing speed. The blind area over tens of kilometers caused by the nonuniform Brillouin response and parasitic amplitude modulation (AM) are crucial factors affecting the signal-to-noise ratio (SNR). Here, a comprehensive performance optimization and substantial enhancement for BOTDA sensors was presented by the direct demodulation of an injection-locked dual-bandwidth probe wave. Injection locking (IL) can completely eliminate the impact of AM noise; dual-bandwidth probe enables self-adaptive pulse loss compensation, thereby intensifying the SNR flatness along the ultralong fiber, and direct probe demodulation can overcome nonlocal effects and allows ∼19.7 dB enhancement of probe input power. Therefore, using only 100 times average, ∼148.3 km sensing, and ∼5 m spatial resolution were achieved with < ∼0.8 MHz standard deviation of Brillouin frequency shift (BFS) over a broad range (∼131.7 km). The reduction in averages was more than 10 times that of the reported majority of long-range BOTDAs. Such performances were achieved without using time-consuming or post-processing techniques, such as optical pulse coding and image denoising. Because this approach is compatible with optical chirp chain technique without frequency sweeping, fast acquisition (0.3 s) was also realized, which has the potential for fast sensing at 3.3 Hz along a ∼150 km fiber.

A method for comprehensive performance optimization of four-leg landing gear based on the virtual equivalent parallel mechanism

Taking-off and landing on unstructured terrain can effectively expand the application of aircrafts. The terrain-adaptive taking-off and landing technology is achieved through adaptive landing gear. The performance of the adaptive landing gear determines the safety performance of the aircraft during taking-off and landing. This paper proposes a comprehensive performance optimization method for four-leg landing gears based on the virtual equivalent parallel mechanism (VEPM). This method associates the motion variables of the parallel mechanism with the terrain data, and combines the original mechanism to form a VEPM. By analyzing the comprehensive performance of the equivalent parallel mechanism, the particle swarm algorithm is used to optimize the dimensions of the landing gear mechanism. The new optimization method can enhance the comprehensive performance of the landing gear mechanism, which contributes to the structural design and optimal control of the terrain-adaptive landing gear.

The Analysis Method of Performance Comprehensive Performance Optimization Design for Multi-body Unmanned Boat

Abstract In order to compare and analyze the comprehensive performance of multi-hull unmanned boats under specific conditions, this paper conducts in-depth research on the multi-objective decision-making theory and intelligent optimization algorithms of boat type design. First of all, this paper establishes the corresponding ship type and resistance database using the response surface fitting method through the drag resistance test of the ship model. Secondly, comprehensively considering the impact of the three major performances of multi-hull unmanned craft on the design of the boat’s speed, maneuverability and seakeeping, a comprehensive optimization mathematical model was established, and the comprehensive optimization design software was adapted. Then, using genetic algorithm, particle swarm algorithm, and chaos algorithm to conduct a preliminary calculation and analysis of the comprehensive performance of the two ship types. By comparing the calculation results, it is concluded that the particle swarm algorithm is the best algorithm among the three intelligent algorithms. Finally, the particle swarm algorithm is used to compare and analyze the comprehensive performance of the two ship types in the multi-hull unmanned craft. It is concluded that the overall performance of the three-hull unmanned craft is better at the same speed and displacement. This paper discusses the pros and cons of the three intelligent algorithms, compares and analyzes the calculation results of each optimization algorithm, and provides a practical way and method for the selection of multihull unmanned boats under the same speed and same displacement.

Comprehensive Performance Optimization of a New Reconfigurable Two-Wheeled Self-Balancing Robot Based on Virtual Equivalent Parallel Mechanism

Comprehensive Performance Optimization of a New Reconfigurable Two-Wheeled Self-Balancing Robot Based on Virtual Equivalent Parallel Mechanism

A new demountable light-gauge steel framed wall: Flexural behavior, thermal performance and life cycle assessment

This paper presents a new demountable and modular light-gauge steel framed (DMLSF) wallboard, which is composed of two C-shaped steel frames, one insulation frame fabricated by timber, expanded polystyrene (EPS) board, orented strand board (OSB) and corresponding connections. The wall proposed in the study can be used in fabricated steel structure or temporary structure. The three-way adjustment joint is developed between the wall and the main structure to adjust the error, which can realize the convenient disassembly and reuse of wallboard. The flexural behavior of the wallboard with varying geometric parameters was investigated experimentally and the numerical model was established to explore the thermal performance of the wallboard. The results show that the failure mode of the wallboard is the local buckling of C-shaped cold-formed steel (CFS) stud, and the ultimate capacities of all the specimens exceed 5 kPa, which can be simply estimated according to the bending capacity of CFS stud. The heat transfer coefficients of tested specimens were between 0.27 and 0.31, and the insulation frame can effectively reduce the heat transfer coefficient. In addition, the life cycle assessment (LCA) method was adopted to study the environmental impact of the wallboard. The steel and EPS contribute the most to the environmental impact and the energy consumption of EPS is the most prominent. Moreover, the synthetical assessment index is proposed to evaluate the comprehensive performance of the wallboard. This paper is desired to provide guidance for the comprehensive performance optimization of demountable components.