Rapid estimates of the risk from potential wildfires are necessary for operational management and mitigation efforts. Computational models can provide risk metrics, but are typically deterministic and may neglect uncertainties inherent in factors dri...
Inverse modeling can estimate uncertain parameters in subsurface reservoirs and provide reliable numerical models for reservoir development and management. The traditional simulation-based inversion method usually requires numerous numerical simulati...
Offshore cranes equipped with active motion compensation (AMC) systems play a vital role in marine engineering tasks such as offshore wind turbine maintenance, subsea operations, and dynamic load positioning under wave-induced disturbances. These sys...
Filter optimization problems involve time-consuming simulations and many variables in the design. These problems require a large amount of computation. This paper proposes an adaptive online updating 1D convolutional autoencoders (AOU-1D-CAE) surroga...
Groundwater LNAPL (Light Non-Aqueous Phase Liquid) contamination source identification (GLCSI) is essential for effective remediation and risk assessment. Addressing the GLCSI problem often involves numerous repetitive forward simulations, which are...
The global exploring feature of the surrogate model makes it a useful intermedia for design optimization. The accuracy of the surrogate model is closely related with the efficiency of optima-search. The cokriging approach described in present studies...
There are deviations between the radio telescope antenna finite element (FE) model, founded on the design stage, and the actual working antenna structure. The original FE model cannot accurately describe the antenna structure deformation characterist...
With the widespread application of generative adversarial networks (GANs) in image generation and content creation, their model architectures and training outcomes have become valuable intellectual property assets. However, in practical deployment, i...
The assessment of ship dynamic stability in waves is crucial for navigation safety. To mitigate accidents, the International Maritime Organization (IMO) has formulated corresponding technical standards. However, evaluating the dynamic stability perfo...
The leader–follower structure is widely used in unmanned aerial vehicle formation. This paper adopts the proportional-integral-derivative (PID) and the linear quadratic regulator controllers to construct the leader–follower formation. Tun...
The thermal design parameters of space telescopes are mainly optimized through traversal and iterative attempts. These optimization techniques are time consuming, rely heavily on the experience of the engineer, bear a large computational workload, an...
The utilization of modal frequency sensors is a feasible and effective way to monitor the settlement problem of the transmission tower foundation. However, the uncertainties and interference in the real operation environment of transmission towers hi...
Droplet ejection technology is widely used in green and intelligent manufacturing. A stable jetting can be defined as no obvious satellite droplets during the whole ejection process, which is of great importance to ensure the quality and efficiency o...
Community detection is widely recognized as a crucial area of research in network science. In recent years, multi-objective evolutionary algorithms (MOEAs) have been extensively employed in community detection tasks. Continuous coding is able to tran...
Surrogate modeling techniques are widely employed in solving constrained expensive black-box optimization problems. Therein, Kriging is among the most popular surrogates in which the trend function is considered as a constant mean. However, it also e...
Kriging surrogate model has extracted extensive attention in reliability evaluation, owing to its excellent applicability and operability nowadays, which confronts with difficulties in balancing the efficiency and accuracy for complicated mechanical...
Numerical models, such as multibody dynamics ones, are broadly used in various engineering applications, either as an integral part of the preliminary design of a product or simply to analyze its behavior. Aiming to increase the accuracy and potentia...
Machine learning has the potential to predict unseen data and thus improve the productivity and processes of daily life activities. Notwithstanding its adaptiveness, several sensitive applications based on such technology cannot compromise our trust...
To reduce the wear and damage of the chute caused by long-term impact of coke, a structure parameter optimization model was established in this paper, which takes the minimum impact force as the objective and the coke-conveying speed as the constrain...
In order to minimize the number of evaluations of high-fidelity (“fine”) model in the optimization process, to increase the optimization speed, and to improve optimal solution accuracy, a robust and computational-efficient multi-fidelity...
The pulse-jet cleaning process is a critical part of the bag filter workflow. The dust-cleaning effect has a significant impact on the operating stability of bag filters. Aiming at the multi-parameter optimization problem involved in the pulse-jet cl...
Computational Fluid Dynamics (CFD) is regarded as an important tool for analyzing the flow field, thermal environment, and air quality around the built environment. However, for built environment applications, the high computational cost of CFD hinde...
As forced-air cooling for heat sinks is widely used in the cooling design of electrical and electronic equipment, their thermal performance is of critical importance for maintaining excellent cooling capacity while reducing the size and weight of the...
A new surrogate-assisted optimization formulation for groundwater remediation design was developed. A stationary Eulerian travel time model was used in lieu of a conservative solute transport model. The decision variables of the management model are...
The increase in urban construction in China has been accompanied by increasing concrete output, which has reached 2250 million m3 in recent years, ranked as the highest in the world. Consequentially, its environmental burden is significant in terms o...
Pipe-insulating joints are common cathodic protection devices in long-distance oil and gas pipeline infrastructures. To ensure safety, they are often designed too conservatively, resulting in large dimensions, high self-weight, and substantial costs....
Due to the inevitable presence of random defects, unpredictable grain boundaries in macroscopic samples, stress concentration at clamping points, and unknown load distribution in the investigation of graphene sheets, uncertainties are crucial and cha...
Natural ventilation and the use of fans are recognized as sustainable design strategies to reduce energy use while reaching thermal comfort. A big challenge for designers is to predict ventilation rates of buildings in dense urban areas. One signific...
Surrogate Modeling (SM) is often used to reduce the computational burden of time-consuming system simulations. However, continuous advances in Artificial Intelligence (AI) and the spread of embedded sensors have led to the creation of Digital Twins (...
Due to the complexity and long-term nature of geological evolution, geotechnical strength parameters exhibit significant spatial variability, which has a crucial impact on slope stability assessment. While traditional numerical methods combined with...
To facilitate the establishment of the probabilistic model for quantifying the vulnerability of coastal bridges to natural hazards and support the associated risk assessment and mitigation activities, it is imperative to develop an accurate and effic...
The significant increase in the speed of high-speed trains has made the optimization of pantograph–catenary parameters aimed at improving current collection quality become one of the key issues that urgently need to be addressed. In this paper,...
A moored spar platform, equipped with various instruments, serves as a crucial tool in hydrological monitoring. However, conducting dynamic analyses of a single spar that endures wind and current requires significant amount of computational time. To...
As the development of floating offshore wind turbines (FOWTs) progresses from offshore to deeper sea, the demands on mooring systems to ensure the safety of the structure have become increasingly stringent, leading to a concomitant rise in costs. A p...
In recent decades, building design and operation have been an important field of study, due to the significant share of buildings in global primary energy consumption and the time that most people spend indoors. As such, multiple studies focus on asp...
The article addresses an approximate solution to the multi-objective optimization problem for a black-box function of a manufacturing system. We employ the surrogate of the discrete-event simulation model of a batch production system in an analytical...
High-strength low-alloy steels (HSLAs) are widely used in the structural body components of many domestic motor vehicles owing to their better mechanical properties and greater resistance. The real production process of HSLA steelmaking can be regard...
In many countries, slope failure is a complex natural issue that can result in serious natural hazards, such as landslide dams. It is associated with the challenge of slope stability evaluation, which involves the classification problem of slopes and...
An optimization model for the optical imaging system was established in this paper. It combined the modern design of experiments (DOE) method known as Latin hypercube sampling (LHS), Kriging surrogate model training, and the multi-objective optimizat...
Under the condition of multiple wells, the inverse problem of two-phase flow typically requires hundreds of forward runs of the simulator to achieve meaningful coverage, leading to a substantial computational workload in reservoir numerical simulatio...
This study developed a data-driven surrogate model based on a deep neural network (DNN) to evaluate gas–liquid multiphase flow occurring in horizontal pipes. It estimated the liquid holdup and pressure gradient under a slip condition and differ...
Traditional numerical models have been widely employed to simulate the transport of multispecies reactive contaminants in groundwater systems; however, their high computational cost limits their applicability in real-time or large-scale scenarios. Re...
To improve the performance of a solid rocket motor (SRM), a multiobjective optimal design method that can consider the structural integrity, internal ballistic performance, and loading performance of the SRM was proposed based on parametric modeling...
In this work we construct a surrogate model using artificial neural networks (ANN) to predict the steady-state behavior of an unmanned combat aircraft. We employ various strategies to improve the model’s accuracy, including the consideration of...
Small-scale thermal treatment systems can provide environmentally improved sewage sludge treatment due to processing sludge locally, which lowers transport costs and emissions. However, the combined effect of confined volume and complex sludge proper...
Ultra-high-voltage (UHV) transmission lines are prone to galloping and oscillations under ice and wind loads, posing risks to system reliability and safety. Accurate aerodynamic coefficients are essential for evaluating these effects, but conventiona...
To meet the increasingly stringent performance indicators of gas turbines, the turbine inlet temperature has increased, and variable geometry turbine technology is widely applied. Therefore, this study developed a quasi-two-dimensional (quasi-2D) met...
Aviation noise remains a key barrier to the sustainable growth of commercial aviation. The advent of emerging technologies, such as urban air mobility, and the renewed interest in commercial supersonic transport aircraft, has only further raised conc...
The paper introduces a novel framework for detecting adversarial attacks on machine learning models that classify tabular data. Its purpose is to provide a robust method for the monitoring and continuous auditing of machine learning models for the pu...
Bridges are essential assets of inland transportation infrastructure; however, they are among the most vulnerable elements of these networks due to deterioration caused by aging and the increasing loads to which they are subjected over time. Conseque...
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