Browse Topic: Optimization

Items (7,593)
Achieving best-in-class Noise, Vibration, and Harshness (NVH) in electric powertrains demands a paradigm shift in development methodology. This paper presents a practice-oriented overview of simulation methods in NVH development methodology for electric drive units. This includes target cascading and multi-objective optimisation, and by attacking NVH at the source using KPIs early in the design cycle, significant reductions in development time and reliance on traditional testbed loops are realised. Machine learning (Neural Network) algorithms are utilized to find the best-in-class design, using multi-objective optimisation as well as refining simulation accuracy by adding tolerance effects while target cascading ensures alignment of system-level performance objectives down to subsystem contributions. Combined, these strategies enable rapid and robust NVH optimisation, using simulation for next-generation electric powertrain development. Several applications and real-life examples
Mehrgou, MehdiGarcia de Madinabeitia, InigoGraf, BernhardGojo, Josef
The vibro-acoustic performance of a vehicle is a critical factor in customer perception of quality and comfort, yet optimizing for Noise, Vibration, and Harshness (NVH)—specifically road noise—presents a persistent challenge in the modern automotive development cycle. While advanced Finite Element Method (FEM) analysis is essential, the increasing complexity and volume of CAE simulation data often overwhelm manual interpretation, potentially leading to prolonged development times or compromises in final comfort quality. To address these challenges, this paper introduces the application of CDH/ACE (Autonomous Computational Experiments), a framework that integrates conventional CAE simulation workflows with advanced machine learning in an iterative, cyclic process. This creates an exceptionally user-friendly and self-correcting system that autonomously defines, performs, and learns from computational experiments. By leveraging machine learning algorithms to build robust predictive models
Visser, Rene
Recent advancements in system-level NVH (Noise, Vibration, and Harshness) development methodologies have improved target cascading and enabled more efficient system-level optimization. Dynamic substructuring facilitates the virtual integration and modification of multiple subsystems and the prediction of changes in overall transfer functions. In practical automotive applications, advanced frequency-based substructuring has been applied to virtually modify system parameters, such as mass and stiffness, at multiple points in a target system, allowing prediction of the resulting effects and optimization of parameter changes without physical intervention. This study extends the methodology by introducing an enhanced substructuring approach capable of addressing not only basic parameter modifications but also large-scale structural changes. The proposed process involves identifying the characteristics of a base system assembly and a target subsystem, decoupling the subsystem from the
Cho, MunhwanBoelens, JelleReichart, Ronde Klerk, DennisAhn, Jiho
To minimize noise caused by interior components rubbing against each other, automotive materials are usually tested in advance with the established stick-slip method according to VDA standard 230-206. This procedure is widely used for soft materials, upholstery and plastics. However, it is limited to constant climatic and selected loading conditions. Contrary, in real application, changing climates and dynamic excitations can nevertheless trigger noise issues even in materials rated as suitable in the prior tests. To address this gap, a new test method has been developed that evaluates the stick-slip behavior of material combinations for a wide range of loading and climatic conditions. Conducted in a climate chamber with a standard stick-slip test bench, the procedure applies sinusoidal excitations, dynamic climatic shifts and advanced data analysis. In addition to the usual results the new method also evaluates realistic scenarios such as starting a vehicle in different seasons or
Fritz, SusanneStrangfeld, Martin
Noise phenomena in automobiles caused by the stick-slip effect are increasingly among the most frequent reasons for customer complaints and therefore represent a critical vehicle quality attribute. To proactively address such issues, stick-slip testing of contacting material pairs is commonly applied during development. However, the predictive capability of current stick-slip test methods remains limited, particularly when highly flexible materials and realistic, stochastic excitation conditions are involved. The flexibility of sealing systems often allows the actual relative motion at the contact interface to be accommodated through adhesion and elastic deformation, thereby delaying or even preventing sliding. To date, this effect has not been represented by any characteristic parameter in conventional stick-slip testing. Instead, existing evaluations focus exclusively on the analysis of occurring stick-slip oscillations. For the initiation of stick-slip phenomena, however, not only
Strangfeld, MartinFritz, SusanneWeber, JensRosell, Anneli
As acoustic requirements for NVH trim components become increasingly constrained by mass, cost, and sustainability targets, traditional approaches to inner dash design based on spatially averaged Transmission Loss (TL) metrics are reaching their practical limits. In fully built vehicles, the acoustic performance of the inner dash is governed by its global insulation capability but also by strong spatial heterogeneity and its interaction with spatially distributed noise sources such as the power unit, gearbox, and tyre-road excitation. This paper presents a test-based methodology for the spatial optimisation of inner dash acoustic performance using reciprocal holography. By applying a calibrated sound power source within the vehicle cabin and measuring the reciprocal response in the engine bay and wheel-arch regions, a high-resolution spatial Transmission Loss “hologram” of the inner dash is obtained under in-situ conditions. The resulting spatial data enables the identification of
Harry, EvanEandi, Giacomo
In this study, we propose a methodology for predicting the acoustic modes and natural frequencies of a sedan using artificial intelligence and demonstrate the feasibility of controlling its acoustic characteristics by modifying the hole distribution of the package tray. In typical sedan structures, the cabin cavity and trunk cavity are acoustically coupled through holes in the package tray. The distribution of these holes significantly affects the natural acoustic modes and frequencies of the vehicle. However, once the exterior shape of the vehicle is finalized during the design stage, options for structural modifications to mitigate noise issues caused by these modes become extremely limited. To address this challenge efficiently, we develop a deep learning-based neural network model trained on data derived from a simplified acoustic analysis model of a sedan that includes a package tray. Finite element analysis is performed to generate acoustic modes and natural frequencies, which
Lee, Jin WooCho, JaehoNam, YounsicHan, Yongha
The present review evaluates recent advances in the development of Welding-Based Additive Manufacturing (WBAM) technologies using arc, high-energy density, solid-state, and hybrid welding systems by providing an interdisciplinary assessment of technological aspects, sensing, process optimization, and multi-process strategies. It is concluded that, in spite of considerable progress in process optimization and control, there exist numerous paradoxes associated with relationships among process conditions, structure, and properties, especially those related to heat input effects on material microstructure and performance. An important finding is the fragmentation of predictive modeling approaches, where physics-based and data-driven methods remain inadequately integrated, limiting generalizability and accuracy. Another important conclusion is related to the dominance of the effect of thermal history and multi-physical phenomena on the mechanical performance of the material produced by WBAM
Santhana Babu, A.V.John Rajan, A.Mishra, AishwaryChakravarthy, P.Jayabalakrishnan, D.
Vehicle fleet decarbonization is a key objective for the coming years, with electrification representing the primary pathway to achieving the targets set by the European Union. The share of battery electric trucks in new registrations has been gradually increasing especially in light and medium size trucks. The replacement rate of diesel long-haul trucks with zero emission trucks is still low due to challenges posed by added complexity and limitations of battery charging. Depot overnight charging is not sufficient to cover the energy needs of a truck covering large distances and careful planning of the route using public charging infrastructure is crucial for an optimized route minimizing extra costs and range anxiety. The current work aims to develop a methodology to propose the optimal charging locations for a given route of a battery electric truck based on nearby stations along the route. Our study uses an open-source optimization algorithm for the fixed route vehicle charging
Perdikopoulos, MichailDoulgeris, StylianosLivitsanos, GeorgiosKazakis, ThomasMellios, GiorgosNtziachristos, Leonidas
Opposed-piston free-piston engine generators (OFPEGs) are emerging as a promising technology for next-generation hybrid and electrified transportation systems due to their high efficiency, reduced mechanical complexity, and improved noise, vibration, and harshness (NVH) characteristics. However, due to eliminating the conventional crankshaft mechanism and directly coupling a free-piston engine with linear generators, performance of OFPEG systems is governed by a strong coupling between piston dynamics, in-cylinder combustion processes, and electrical loading conditions. This coupling presents substantial challenges for system design, control, and optimization, limiting the further development and application of OFPEGs. Existing researches lack a comprehensive numerical model that integrates detailed in-cylinder thermodynamic process with control system of linear generator, and quantitative analysis of the effect of piston motion trajectory on system performance remains insufficiently
Wang, JiayuMorandi, NicolaLucchini, TommasoFENG, HUIHUAJia, BoruRen, Peirong
This digital standard is a requirements extract of AS4159 Specification For An Automated Interchange Of Standards Data. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
This digital standard is a requirements extract of AS50881H Wiring Aerospace Vehicle. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
This digital standard is a requirements extract of AS861C Minimum General Standards for Oxygen Systems. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
This digital standard is a requirements extract of AS5127D Aerospace Standard Test Methods for Aerospace Sealants Methods for Preparing Aerospace Sealant Test Specimens. This file contains a general requirements extraction as well as files that are optimized for use with Doors Classic, Siemens Polarian, and PTC.
The integration of Electric Vehicles (EVs) as active grid resources represents a pivotal shift towards decarbonization. However, the implementation of effective Vehicle-to-Everything (V2X) services faces technical challenges regarding interoperability, predictive management, and battery health preservation. This work presents a comprehensive system design and research methodology developed within the framework of the FLEXV2X project, aimed at addressing interdependencies within a unified bidirectional charging ecosystem. The proposed scientific framework addresses two complementary timescales. At the device level, the study details the modelling and optimization of bidirectional converters, focusing on control algorithms designed to ensure robust dynamic response and efficiency. Building upon this hardware foundation, the paper describes a system-level optimization strategy. By employing open-source cyber-physical modelling, the architecture simulates complex EV-grid interactions. This
Lutzemberger, GiovanniBarater, DavideCeraolo, MassimoFera, CesareLeaver, IanPasini, Gianluca
Initial weight estimation from Top Level Aircraft Requirements (TLAR) is a critical first step in aircraft design, yet existing empirical methods are inadequate for novel configurations such as those using Liquid Hydrogen (LH2) or Sustainable Aviation Fuels (SAF). This paper presents a hybrid methodology for top-level weight estimation of such unconventional aircraft. The approach is based on modifying a conventional baseline aircraft, integrating a new statistical model with component-specific weight estimations. A multivariate regression model to estimate the empty weight fraction (We/W0) was developed from a dataset of 44 conventional aircraft, yielding an R-squared value of 0.833. This statistical model was integrated with physics-based models for novel components, including cryogenic fuel tanks and fuel systems. The methodology accounts for iterative changes to fuselage structure and parasitic drag. Four configurations were analyzed: fuel types being Jet A1, SAF, LH2 with aft
Goyal, Tushar
To develop magnesium matrix composites, ceramic silicon nitride (Si3N4) particles are added to the magnesium (AZ31) matrix at 2 wt.%. The composite is produced via disintegrated melt deposition vacuum-stir-casting procedure. Microstructural studies reveal the presence of Si3N4 particles and their uniform spreading. An L9 orthogonal array, planned using Taguchi’s experimental design, is selected for three wear parameters; axial load (AL), rotational speed (RS), and time duration (TD) with trials as per the G99 standard in the pin-on-disc apparatus to assess the wear resilient of the composite. Experimental results show an increase in axial stress, and wear loss (WL) increases dramatically. Because the area of contact shrinks as RS increases, WL diminishes dramatically. When the AL is low, the friction coefficient (CoF) increases, and when the AL is large, CoF drops. When the RS is increased, CoF decreases. To optimize multiple responses effectively, the TOPSIS (Technique for Order
Senthilkumar, N.Dhinakar Raj, C K
Dynamic soaring is a flight technique that exploits wind shear for sustained flight. It is commonly observed in birds such as albatrosses and holds significant potential for unmanned aerial vehicle (UAV) missions. Previous research has primarily focused on trajectory generation using direct optimal control or differential flatness. This paper proposes an enhancement to the existing six-degree-of-freedom (6-DOF) trajectory generation method based on differential flatness. The proposed formulation includes sideslip and accounts for all stability and control derivatives. A Vortex Lattice Method (VLM) solver is then used to compute steady aerodynamic forces and moments, which are compared against the constant-derivative-based trajectories. To assess the validity of the constant-derivative assumption, a 6-DOF UAV model is simulated in a dynamic soaring orbit with stability augmentation provided by a Linear Quadratic Regulator (LQR). The observed divergence in this simulation highlights the
Swaminathan, Bharath
Digital engineering practices in aerospace increasingly require closely connected and traceable analysis workflows rather than isolated finite element tasks. Traditional FEA methods remain effective, but they involve considerable manual effort during pre- processing and post-processing, making rapid iteration difficult. Finite Element Analysis of STructures (FEAST), an indigenous finite element analysis software developed by Vikram Sarabhai Space Centre (VSSC) ISRO, offers structural analysis capabilities through a command-based architecture, yet its manual operation limits its use in automated studies. This work develops a flexible scripting-driven framework that links geometry creation, load-case definition, solver execution, and result interpretation within a unified digital engineering pipeline. The framework automates repetitive tasks, incorporates Design of Experiments (DoE) for systematic parameter variation, and supports sensitivity and automation studies. Its performance is
Gupta, ShivangiT J, Raj ThilakP, Deepak
The increasing demand for safety and reliability in aerospace applications necessitates rigorous testing of aircraft components, including light units, for explosion proofness. Traditional explosion proofness tests are destructive, expensive, and time-consuming, requiring significant resources for test setups and prototypes. To address these challenges, this research presents a numerical methodology using Computational Fluid Dynamics (CFD) simulations to investigate the explosion proofness for aircraft light units. The primary motivation of this study is to establish a computational framework that supports early-stage design screening, reduces the number of physical prototypes, and enhances understanding of explosion behavior before formal qualification testing. This work contributes to advancing engineering practices in the aerospace industry by demonstrating the efficacy of CFD simulations in evaluating and enhancing the explosion proofness of light units. The proposed CFD model
Selvaraj, SugumaranNataraja, Prabhu
The study proposes the use of Carbon Fiber Reinforced Plastic (CFRP) sandwich composites configurations for structures interfacing cryogenic tankages. To address the design challenge posed by high thermal contractions in metallic tanks after cryogenic propellant filling, the study incorporates slits near the tank interfaces. Additionally, to minimize the transfer of cryogenic temperatures into these interfacing parts, the sandwich structure features interface end attachment made of thermally insulating Glass Fiber Reinforced Plastic (GFRP) material. Analytical and Finite Element (FE) studies were conducted on a typical cylindrical cryogenic intertank structure to demonstrate the proof of concept. These studies included analytical design using MATLAB based codes, parametric analyses with simplified shell element models and detailed 3D sector models using solid elements. The parametric studies assessed the effects of the number and dimensions of slits to achieve an optimal design, while
Bhalerao, Sandesh PopatGupta, Yogesh KumarMadhukumar, P.
Static electricity is an electrical imbalance on the surface of a material which can interact with other components having same or different materials. Fluid flow within the hose assembly generates static voltage due to friction caused by fluid flow in pipes, that needs to be appropriately quantified and dissipated. Accumulation of such static charge may lead to sudden discharge leading to spark generation. Spark generation around fuel flow might lead to system failure and failure in aircraft engines. Test experiments were conducted to analyze static voltage generated in hose assembly due to fuel flow with the objective that voltage achieved is within the acceptable range to avoid ESD (Electrostatic Discharge) failure. Procedure includes flow rate monitoring and voltage measurement using fuel as test fluid. The testing revealed that the curvature of the hose affects the readings, highlighting the importance of consistent meter alignment. Using a grounding strap is essential to prevent
Waghmare, Shashank
The rapid growth in the number of aircraft and pilots emphasises the need for an AI-enabled training framework that can offer precise, automated examination of flight manoeuvres. This will be useful in optimising the pilot's training efficiency and minimising iterations of the conduct of flight manoeuvres, thereby reducing the training time of the pilot for a flight. A general framework is developed that can be used for all kinds of flight phases and aircraft types. A pre-trained machine learning model is designed using a supervised learning technique, Random Forest, to recognise different manoeuvres. Various statistical parameters, such as mean, standard deviation, kurtosis, skewness, etc., of several flight parameters were used as the input features to train the Random Forest classifier. In the present work, the classifier is trained using several actual flight test data manoeuvres, and is also supplemented with simulated manoeuvres. The achieved gross accuracy for manoeuvre
Sahu, AkashC, PoornimaC, AravindhKaliyari, DushyantTK, Khadeeja Nusrath
In modern engineering, compressors play a vital role across numerous industries by enabling the delivery of fluids at elevated pressures for a variety of applications, including HVAC systems, aircraft engines, and process industries. The performance of centrifugal compressors is characterized by parameters such as flowrate, efficiency, and pressure rise. Traditional methods of evaluating compressor performance, such as physical testing, are often time-consuming and costly, making them less practical for iterative design or optimization. Advancements in Computational Fluid Dynamics (CFD) have provided a faster and more cost-effective means of assessing compressor behavior. This study presents a comprehensive CFD-based analysis of a two-stage centrifugal compressor utilized in HVAC applications aimed at predicting its performance, that is, flow factor vs head factor and flow factor vs efficiency for given rotational speeds and inlet guide vane (IGV) angle positions. Focus is on
Turaga, Vijay KumarAadi Gopalakrishna, PradeepGugulothu, Sampath
The mechanical performance of short fiber-reinforced plastic (SFRP) components is highly sensitive to fiber orientation, which is significantly influenced by the injection gate location during the molding process. Traditionally, gate placement decisions are driven by warpage minimization strategies, often overlooking mechanical performance under diverse load cases. This research introduces an automated workflow within Digimat-MS that integrates injection gate optimization into the early design phase, leveraging Integrated Computational Materials Engineering (ICME) principles. The proposed methodology enables engineers to upload either Marc, Abaqus or Ansys input decks, select a component of interest, assign material cards, and define gate scenarios. A Design of Experiments (DOE) is then executed locally or remotely, allowing Digimat to evaluate multiple gate configurations. The system aggregates results and identifies optimal gate locations based on the initiation of failure under
Kauthale, TanmayMadhavan, VinaySoni, Ganesh
Achieving zero-waste manufacturing in aerospace requires a shift from end-of-pipe waste mitigation toward circular design principles embedded early in product development. This paper presents a practical framework for integrating circularity into aerospace systems through five design pillars: design for modularity and disassembly, material substitution to enhance recyclability, waste segregation and characterization, component-level circularity readiness scoring, and collaborative supplier engagement. To operationalize this approach, a Circularity Readiness Assessment Tool (CRAT) is developed to evaluate design alternatives against criteria such as disassembly ease, material recyclability, manufacturing waste potential, end-of-life recovery pathways, and supplier take-back mechanisms. The framework supports multi-criteria decision-making by complementing traditional aerospace design drivers including weight, performance, cost, and safety. The methodology is demonstrated through a case
S, Chaitra
To enhance the economic efficiency and operational security of distribution grids, this paper develops a reactive power optimization model that incorporates distributed power sources. The model aims to minimize the costs of reactive-load compensation equipment, reduce voltage deviations, and lower network losses while satisfying operational constraints. To overcome the common drawbacks of the standard genetic algorithm—such as limited optimization precision and a tendency to converge to local optima—four improvement strategies are introduced. These include an enhanced encoding scheme, an initial population generated via opposition-based learning, an elite retention strategy, and the adaptive adjustment of crossover and mutation rates. Together, these modifications strengthen the algorithm’s global search capability. The proposed approach is validated using the IEEE30 node system. Compared with both the conventional genetic algorithm (GA) and an adaptive genetic algorithm, the improved
Wang, MaozeXiao, WenyuLiu, YujiaXu, ZhengweiXia, Yinyong
Layout optimization is one of the most effective approaches to reduce the power loss induced by turbine wakes. However, the performance of a wind farm is strongly affected by the inflow direction. This paper conducted a sensitivity analysis on a realistic wind farm, Lillgrund Wind Farm, to investigate the sensitivity of inflow direction on the power production of the initial layout and optimal limits. A wake model considering ambient turbulence intensity is adopted together with the wake superposition method to efficiently resolve the flow field in the wind farm. The results indicate that the power production of the initial layout had a significant discrepancy under different inflow directions, and relies on the consistency of inflow direction and layout array directions. The feature of the two main directional sectors is observed from a realistic wind rose. Therefore, two-sector wind roses are adopted in optimization, and the angles of sectors vary among 51 cases. After optimization
Yang, KunDeng, Xiaowei
With the introduction of China’s dual-carbon goals (carbon peak and carbon neutrality), renewable energy has experienced rapid development in the country, particularly wind energy, which has established a pivotal role within the new energy sector. However, the inherent fluctuations in wind power generation pose significant challenges to maintaining grid stability and operational reliability. In power systems where the proportion of installed wind power capacity has significantly increased, the allocation of flexible resources becomes crucial. These resources help the system adapt to fluctuations in wind power generation and load demand, avoid wind power curtailment, and reduce costs. In addition, energy storage enhances grid flexibility and stabilizes renewable energy, but is constrained by high costs. Therefore, optimizing energy storage allocation and improving its economic efficiency have become urgent issues. This study focuses on flexibility adequacy assessment and resource
Peng, JianWei, JinpengZhu, ZhengyinHu, JianminLi, YuxiangMiao, GangZhang, Huaide
This study investigates the unsteady aerodynamic response, wake evolution, and vortex dynamics of an ultra-large floating offshore wind turbine (FOWT) under coupled motion–wave conditions. A high-fidelity aero–hydrodynamic CFD model is employed for the IEA 22 MW reference turbine. Platform pitch and surge motions are prescribed via sinusoidal functions, and wave conditions are independently introduced by considering two representative sea states (H = 4 m and 7 m) and a no-wave case. Results show that pitch and combined pitch–surge motions significantly amplify unsteady aerodynamic effects, increasing peak power from 81.1 MW (P5S0) to 92.6 MW (P5S5), with periodic negative power output and severe dynamic stall. Under strong motion, waves further raise peak power to 93.4 MW (H7P5S5), indicating a coupled amplification effect. Dynamic stall is mainly triggered by pitch motion, expanding in scope and duration with motion amplitude; wave effects on stall remain limited. Platform motion also
Xie, BinSun, HaiyingChen, Ye
Based on the multi-objective hierarchical optimization solution method, this paper takes both system balance and scheduling economy into account, and constructs a hierarchical collaborative optimization model for the multi-energy complementary system of offshore energy islands. To address the impact of the volatility and randomness of offshore wind farm clusters on the scheduling of energy island systems, the Stochastic Model Predictive Control (SMPC) method is adopted to optimize and solve the scheduling of offshore energy islands. This paper innovatively proposes a scheduling method based on adaptive variable-step stochastic model predictive control. In the rolling optimization process of SMPC, this method tracks the real-time scheduling deviation degree through the deviation reference coefficient and changes the rolling optimization step size. It solves the problems of insufficient scheduling accuracy and being trapped in local optimization in the rolling optimization process of the
Huang, HaochengZhang, JinqiZhou, FengfengYan, QihuiXu, ChangYin, Gaojun
As the trend toward larger wind turbines continues, the increasing length of blades imposes higher demands on their structural properties. And in actual engineering, wind turbine blade accidents occur frequently. Consequently, ultra-long flexible blades at the hundred-meter scale typically employ composite materials. However, due to the high cost of composites, it is necessary to minimize blade weight to control costs. This study utilizes the MATLAB simulation platform combined with pattern search algorithms to optimize the composite layup of large wind turbine blade structures. The structural properties of the optimized design are then compared and analyzed against those of the reference structure. Simultaneously investigate the impact of different loads on the optimization results. The results demonstrate that the pattern search algorithm can optimize blade layup thickness, spar chordwise position, and spar width, yielding a new blade structure with improved performance. During
Cao, GuangchuanGuo, XiaMeng, Hang
In the context of the global active response to climate change and the strong advocacy of green development, China’s energy industry is demonstrating a steadfast commitment to low-carbon transformation. In this process, green power trading has gained significant development by virtue of its unique advantages and potential. In this process, green power trading has gained significant development by virtue of its unique advantages and potential. The core objective of the Pinglu Canal Project, a pivotal initiative promoting green and low-carbon development in the region, is to establish a “net-zero carbon” initiative by facilitating the supply of green energy throughout its entire life cycle. This initiative is designed to promote a green and low-carbon transition. This paper conducts an in-depth study on the green power supply path during the construction period of the Pinglu Canal project, and proposes four practicable options. In order to scientifically and objectively determine the
Huang, ZeyiWei, YuchenLi, XiayangWang, Cuixian
Taking China’s five northwestern provinces as the study area, this paper investigates the spatial-temporal interactions among carbon emissions, passenger transport, and freight transport from 2010 to 2020. An entropy-weighted composite index is constructed for each system and integrated into a coupling coordination degree model to quantify interaction. It is found that (1) the average annual growth of provincial coupling coordination degree is 4.7%, but the gradient difference between regions is significant, and the extreme difference of coupling coordination degree between east and west reaches 4.5 times in 2020; (2) Spatially, it shows a unipolar leading pattern, with Shaanxi achieving a significant decrease in carbon emission intensity and Qinghai achieving a lesser coupling coordination degree of 23% in Shaanxi due to the high proportion of highway freight transport and single energy structure; (3) the driving mechanism analysis shows that the improvement of transport network
Qian, YongshengLi, ShaoyuanZeng, JunweiHe, Qingling
The design and analysis of the wave plate of the tank body of the low-temperature liquid nitrogen tank car are carried out. According to the design method of the empirical formula, the 0.43 MPa low-temperature mobile liquid nitrogen tank body wave plate with the working temperature of -196°C to -178°C is optimized. According to the analysis and design standards, the stress distribution law of the mobile liquid nitrogen tank body under the forward impact condition is analyzed by the method of numerical analysis. The results show that the stress value will gradually increase near the junction of the tank body and the support, and the parts such as the head, the pad, the angle steel ring, and the Z3848 glass steel pipe meet the requirements of the analysis and design standards. At the same time, the first six orders of the natural mode vibration frequency of the tank body are analyzed, which provides a reliable and effective data analysis for the optimization design of the low-temperature
Ding, XuqiangNi, YiweiGu, ChenYan, DongdongXu, ZhiquanWang, Qi
This article describes multi-body dynamics simulation to investigate door jitter issues caused by the limiter during door operations. A simulation model integrating a rigid limiter and a flexible door-body system was developed to replicate the dynamic process of wide-angle door opening/closing. Through iterative refinements—including correlation of simulation results with test data, optimization of internal door connection methods, and solid-element hinge modeling—simulation accuracy was improved to over 89.7%. Using the validated model, quantitative metrics were established to evaluate door jitter severity. Key parameters that influence the door operation smoothness were identified, and an optimization scheme was proposed for a specific vehicle model, incorporating slope-holding performance requirements under hill-parking conditions. Finally, prototype testing validated the approach’s effectiveness. The developed simulation method provides a technical foundation for virtually
Xiao, YongfuDeng, JianjiaoLi, JingtanYang, TaoHou, HangshenHan, ChaoGao, MengWang, YiqiLiu, Yihong
When simulating spray atomization process involving VOF method, a core problem is the conflict between high grid detail and limited computer power. Although VOF and DPM methods have recently been coupled to reduce computational cost, their application in practical engineering calculations still imposes a considerable computational burden. To solve this, a better adaptive mesh refinement (AMR) plan is put forward. This plan uses a 0.2 mm initial grid (twice the usual 0.1mm) and allows refinement up to four levels. This improved technique makes high computational efficiency for large-scale simulations. Two types of nozzles are employed to evaluate the proposed method. However, for circular nozzles, the new method does not increase calculation speed, while lowers the accuracy of the simulation.In contrast, for square nozzles, it greatly boosts computation speed and keeping high accuracy. This makes the technique a useful tool for modeling transverse jet atomization in industry. Overall
Zhou, TaotaoMa, MingZhang, HaitaoZhang, FenganChen, XianhuiChen, QiXia, Hongwei
The stable operation of islanded DC microgrids is conditioned by two essential objectives. One is to maintain the bus voltage at its nominal value, and this can ensure system stability. The other is to achieve cost-effective power allocation among distributed generation units, which guarantees economic efficiency. These two objectives are often conflicting. Adding droop control to the voltage and current dual closed-loop control can achieve primary current sharing. However, it inevitably introduces steady-state voltage deviations on the DC bus and results in inflexible or not optimal power sharing. To resolve these inherent limitations, this paper proposes a innovative distributed secondary control strategy. The method is designed to meet both requirements within a unified framework. In the primary control layer, it uses adaptive droop gains to optimize power distribution in real time based on changing load requirements which enables distributed generation units to achieve cost
Sun, WeiShe, DunjunYu, JinzhuYuan, WeiboPeng, BoZheng, Yingchun
As a densely populated public place, exhibitions feature spatial layouts with multi-area linkage and instantaneous crowd flow mutations. Thus, developing a crowd flow early warning system adapted to exhibition dynamics is a key focus at the public safety and smart exhibitions to avoid risks like local congestion-induced stampedes. In general, two core challenges in exhibition crowd counting: 1) Key dynamic gathering information is hidden in high frequency components, but no correlation mechanism between frequency components and scene has been established; 2) Instant crowd gatherings cause high-frequency local density mutations, leading to time delays and spatial ambiguity of dynamic signals. To solve these, we propose a novel Crowd Counting Network for Risk Early Warning in Exhibition Scenarios with two core modules: 1) A bidirectional feature filtering module optimizes frequency information through low-frequency suppression to reduce redundancy and high-frequency activation to
Zhang, JinZhang, WanyueYuan, JingjingChen, ZhenGu, Dazhi
To address the challenge of balancing voltage support and current limitation in grid-forming converters (GFCs)—a challenge induced by the uncontrollability of active power during transient faults in microgrids and weak grids—a low voltage ride through (LVRT) strategy utilizing adaptive virtual impedance with a variable resistance-to-inductance ratio is proposed. This strategy is designed to maximize the satisfaction of reactive power support and current limiting characteristics. By adaptively generating virtual impedance based on changing line parameters, the method enables adaptation to large disturbance conditions involving variations in line impedance and Short Circuit Ratio (SCR). First, a transient model of the virtual impedance for GFCs is established to clarify the transient instability mechanism. During the transient period, the power loop is controlled to prevent power angle divergence. Second, the influence mechanism of virtual impedance on reactive current and output current
Pang, BoYang, XiangzhenLiu, Fang
While large language models (LLMs) offer a convenient natural language interface for logistics optimization problems, it remains challenging to directly generate reliable mathematical models and executable code from unstructured text requirements. LLMs tend to produce invalid constraints or syntactically incorrect code. In addition, traditional logistics optimization methods lack the flexibility to adjust warehouse rules or operational goals without manual expert intervention. To address these issues, we propose LOOP (a Language-Model Orchestrated Optimization Pipeline), which automatically translates natural-language requirements into optimization algorithm code while retaining the rigor of classical models and solvers. LOOP leverages task-specific agents to construct accurate mathematical models and adopts a difference-driven code generation approach. First, it synchronizes model changes into executable code via semantic mapping and ensemble difference analysis. Second, it
Ding, RuiqingLi, QianyingLi, Xiaojian
In order to achieve the research objective of simultaneously improving the air volume and reducing the noise of centrifugal fans, a combination of orthogonal experimental design, BP neural network modelling and multi-objective genetic algorithm (NSGA- II) was used to find the optimal method, and the worm tongue placement angle φ, worm tongue radius R, expansion angle θ and outlet expansion section height L of the worm casing were selected as optimization variables. The air volume and noise of the centrifugal fan under the design working condition were calculated by non-constant and constant calculations, and the air volume and noise were used as the optimization objectives. The results demonstrate that, compared to the initial design, the optimized fan model achieved a noise reduction of 10.99 dB and an airflow increase of 1.76%. Furthermore, the amplitude of the pressure pulsation coefficient at the blade passing frequency was significantly reduced at the monitoring point near the
Huang, GuoxingZhang, WeihongLi, Weichang
In this paper, the design and process research of uniform filling linear trajectory for filament wound hydrogen storage tank with unequal polar holes are carried out. Firstly, by optimizing the slip coefficient, the winding angles of the left and right heads are smoothly and continuously transitioned to the cylindrical section. We study the necessary conditions for achieving the central angle of uniform filling, and calculate the tangent points of the trajectory line based on the continuous fraction principle. Meanwhile, the slip coefficients at the left and right ends that satisfy stable winding and uniform covering are determined. Based on the equal contour constraint conditions, we analyze the motion trajectory equation of the four-axis winding machine and convert it into the corresponding machine code for actual winding operations. Experimental results show that stable winding of fibers on the surface of the unequal-polar-hole mandrel is achieved, and uniform filling and winding
Chen, BaosenFu, JianhuiCao, XuewenYu, Libin
As the “digital brain” and core foundational support for the development of intelligent transportation and connected vehicles, the performance of data centers directly determines the operational capability of intelligent transportation systems. In the process of advancing the vehicle-road-cloud collaborative architecture, the demand for high-performance computing power in data centers has experienced explosive growth. The substantial increase in computing tasks has posed severe challenges to thermal management, making efficient and reliable cooling systems an indispensable core component. Centrifugal compressor water-cooling units are the mainstream cooling solution for large-capacity scenarios, and their design optimization is crucial for improving the energy efficiency and performance of the entire cooling system. This paper proposes a one-dimensional performance prediction method for centrifugal compressors based on an empirical loss model, and realizes the iterative calculation of
Zhu, MinhaoJiang, BinLi, MinZeng, ZihuiGu, Yunhui
The rapid development of autonomous driving technology has brought emerging opportunities to optimize the omnidirectional vehicle driving performance. However, its compliance with driving habits directly determines its social acceptance. Therefore, how to balance consistency between performance improvement and driving habits has become an important bottleneck restricting the rapid promotion of autonomous driving technology. Manual driving vehicles mostly focus on the safety of both longitudinal and lateral movements, and cannot cope with the vertical movement, let alone the performance of economy, comfort, and efficiency. In this context, this paper proposes an anthropomorphic trajectory optimization method incorporating vehicle omnidirectional dynamic characteristics and corresponding driving habits. Firstly, this paper explores vehicle dynamic characteristics in longitudinal, lateral, and vertical directions, and reveals the coupling effect of motion states during driving
Liao, PengZhang, DefengNing, DonghongLi, SijiaWang, Tao
Accurate prediction of load distribution in multi-bolt metal–composite joints relies heavily on high-fidelity modeling of single-bolt joint stiffness. Current models, however, inadequately capture the complex effects of bolt–hole clearance, including delayed load take-up and reduced bearing chord stiffness, as well as multi-interface friction interactions. To overcome these limitations, quasi-static tests were conducted on single-bolt, single-lap aluminum–CFRP joints with varying clearances. By integrating experimental findings with an analysis of the load-transfer mechanisms, we identified five distinct loading states and formulated corresponding analytical load-deformation equations along with explicit transition criteria, culminating in a novel piecewise-linear stiffness model. Enhancements over traditional tri-linear models encompass: (a) subdivision of the transition region into separate local and global slip phases, facilitating an accurate representation of asynchronous slip
Liu, HaolongSun, QingpingLiu, YangZhao, QiLiu, Yue
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