Load Model Research Articles

Constructing nonlinear data-driven models from pitching wing experiments using multisine excitation signals

Accurate modelling of unsteady nonlinear aerodynamic loads is crucial for the effective design and control of aerodynamic systems. Data-driven modelling approaches have emerged as powerful tools for capturing intricate system dynamics without prior knowledge of the underlying physical principles. This paper focuses on the construction of nonlinear data-driven models for pitching wing systems using multisine excitation signals and their relative merits compared to swept sine signals. The polynomial nonlinear state-space (PNLSS) modelling framework is used, which has been proven in the system identification community to offer flexibility and richness in representing diverse nonlinear phenomena. Data are gathered with a dedicated experimental wind tunnel setup. A NACA 0018 wing is made to oscillate in pitch according to a swept sine and a multisine with a frequency up to 2 Hz. The experiments are repeated to cover the attached flow, light stall, and deep stall regimes. PNLSS models are trained on multisines and benchmarked against models trained on swept sines to assess their comparative performance. Then, all models are successfully cross-validated using single sine data at different angles of attack. We conclude that one single data-driven model can accurately represent the lift force across different linear (attached flow) and nonlinear (light and deep stall) operating regimes.

СПРОЩЕНА ІМІТАЦІЙНА МОДЕЛЬ НАВАНТАЖЕННЯ В ЗАМКНЕНІЙ МЕРЕЖІ КОМУТАЦІЇ ПАКЕТІВ

An approach to simplified simulation modeling of packet switching network load has been developed. The simulated representation of network processes is based on a simplified mathematical model of the packet switching network, which is based on a dis-cretized description of the load states of the network nodes and corresponds to the repre-sentation of the current state of the network in the tasks of managing its load. Changes in the node's filling state are modeled as a process of reproduction and death, and in the full load model, two factors of change are taken into account: the node's exchange of load with network users and transit load flow passing through it. To study an artificially se-lected "part of the network functioning process" - an approach to transit load modeling in a load-locked network is proposed. The approach allows for significant simplifications and ensures the leveling of the negative impact of simplifications on "load closure" (en-sures the rule of constant amount of load in a closed network). The developed simulation model, firstly, creates the basis for the improvement of the complete model, and secondly, it is convenient for working out routing algorithms when analyzing them from the point of view of indicators of the ability to "influence" the load in the network. The obtained re-sults are generalized, but attention is focused on the example of satellite packet switching networks.

Mechanical characterization of lining under three-dimensional complex load during shield posture adjustment

The shield tunneling method is widely used in urban underpass construction. However, research on the mechanical characteristics of segments during construction is insufficient. Throughout the shield tunneling construction process, segments undergo a diverse range of loads, and their modes become complex. During the adjustment of the posture of the shield machine along a curved path, segments must withstand three-dimensional uneven loads from the shield tail brush and extrusion of the shield shell, in addition to conventional loads. Thus, this study delves into the mechanical characterization of the lining during shield posture adjustment. First, three-dimensional refined models of the longitudinal and circumferential joints were established to investigate their bending and shear mechanical properties. Using the joint and shield tail brush stiffness models, a nonlinear spring-connector-shell model was developed for the mechanical analysis of segments during posture adjustment. Subsequently, a three-dimensional segment load model was formulated for the construction period. The segment response under the influence of different posture adjustments was examined using a numerical model of a tunnel subjected to a complex three-dimensional load. Furthermore, a multistage model of the segment response under various posture adjustments was established. This model serves as a valuable reference for engineering applications.

Research on the Support Performance of Internal Feedback Hydrostatic Thrust and Journal Bearing Considering Load Effect

This study aims to analyze the impact of uniform and eccentric load conditions on the performance of internal feedback hydrostatic thrust and journal bearing. Two distinct models are established: a three-degrees-of-freedom uniform load model and a five-degrees-of-freedom eccentric load model. The support stiffness, overturning stiffness, and flow rate for both thrust and journal bearings are calculated. Additionally, numerical analysis is conducted to examine the influence of oil film thickness, inlet pressure, and restrictor size on the operational characteristics of the bearings, revealing the interplay between an eccentric load and journal bearing speed. The validity of the theoretical algorithm is verified through finite element simulation. The research outcomes hold significant guiding implications for the design and application of internal feedback hydrostatic bearings.

Design and Development of Mathematical and Thermal Load Modelling for Induction Heating Systems

Complex systems can be modelled and their performance can be anticipated with the help of current computers and software tools that are applicable in real-world situations. The IH system is capable of being modelled and put through analysis in two distinct domains. The modelling is compatible with the research and applications in their entirety, including the particular control circuits and converter systems under consideration. The use of electrical modelling makes it possible to analyse the features of the IH load and to examine the variations in the parameters in order to determine the impact of load variations. In order to gain an understanding of the load's flow and thermal distribution, thermal modelling is a crucial component of this study. For the purpose of analysing the performance of the coil in terms of flux and temperature from its comparable model, the COMSOL Multiphysics software that is utilised is utilised.

Assessment of the bearing capacity of variable profile piles in soil using static load model tests on a testing apparatus

The paper presents the results of the study of the proposed type of variable profile piles. The proposed type of piles is reinforced concrete driven piles segmented in length. Each subsequent section has a radial displacement along the axis of symmetry relative to the previous section. The positive effect of the performance of the proposed pile is to change the nature of the lateral contact of the pile with the soil, and to increase the drag of the soil. The conducted research is aimed at solving the problem related to the relatively low bearing capacity of traditional square section piles. The research was carried out by the method of model tests of piles on a test bench (tray) at a scale of 1:10. The tests were performed for variant pile types in comparison with a standard square section prismatic pile. The adopted dimensions of the pile model allow the use of this tray without the influence of its boundary conditions on the stress-strain state of the soil. A total of 42 tests were performed, 3 tests for each type of piles compared. Evaluation of pile bearing capacity was performed by static loading of pile models with vertical indentation load until failure. According to the results of the investigations, the resistance values of the compared pile types in the soil were obtained, as well as the dependence of bearing capacity changes on the section dimensions and on the rotation angle. According to the results, the optimal pile solution was selected. The bearing capacity of the proposed optimal pile solution exceeds the bearing capacity of the standard driven pile by 22 %. The results obtained allow us to conclude about the influence of the technological solution of the proposed pile type on its serviceability in soil conditions

Dynamic behaviour of bridges under critical conventional and regular trains: Review of some regulations included in EN 1991-2

In the field of structural analysis dedicated to the study of vibrations of high-speed railway bridges, one reference load model is the well-known HSLM-A, which limits of validity are stated in Eurocode EN 1991-2, Annex E. In a recent paper published in the Journal of Rail and Rapid Transit, the authors investigated the degree of coverage provided by HSLM-A to critical articulated trains. Now in the present article, the authors have extended those analyses to critical conventional and regular trains as well. This is an important aspect because HSLM-A as such is an articulated-type model, so it is of interest to understand how it deals with covering the various resonance phenomena generated by other train types. Therefore, the main goal of this work is to establish whether the conventional and regular trains that stem from the validity rules given in Annex E/EN 1991-2, produce vibratory effects that are duly covered by HSLM-A. Following the aforementioned validity rules, one first aspect analysed is the importance of near-to-integer wheelbase ratios in the coupled vibrations produced by conventional trains. Subsequently, seven realistic, conventional and regular high-speed train models have been synthesised; these models have been made publicly available in Mendeley Data, and comprise almost 3800 different sequences of axle loads. Finally, the response of simply-supported bridges has been analysed with a view to compare the seven synthesised models versus HSLM-A. The exceedance and required speed increase have been computed for both displacements and accelerations, in a comprehensive ensemble of spans and speeds. The results provide a diagnosis of the degree of coverage of HSLM-A with respect to those conventional and regular trains compliant with Annex E/EN 1991-2.

Global sensitivity analysis of the maximum live load and its applications

The design live loads are determined by the probability distribution of the maximum live load, which is influenced by the amplitudes and time intervals of various sustained and extraordinary loads. If the relative impact of different input variables on the maximum can be clarified, more targeted load surveys and modeling can be achieved. However, there is currently no global sensitivity analysis that simultaneously considers all input variables. In this study, the probability density function of the maximum live load is determined using the load coincidence principle and probability density evolution method. The relative entropy is employed as a measure for conducting a global sensitivity analysis across five common building occupancy types. The results indicate a significant imbalance in the impact of different input variables. The load amplitudes have a much greater effect than the time intervals. Among various load amplitudes, those related to the extraordinary loads often have the most significant impact. Regarding the time intervals, the occurrence intervals corresponding to the extraordinary loads caused by furniture stacking and normal crowding consistently have the least influence. For the time intervals with minimal impact, it is suggested to treat them as deterministic values in the live load modeling. This treatment has a negligible impact (not exceeding 10%) on the mean and upper fractile of the maximum, which are generally used for design in load codes.

Power generation–network–load–energy storage co-planning under uncertainty

With the aggregation of renewable energy in the power system, the uncertainty caused by the renewable energy affects the planning and operation of power systems. Meanwhile, the existing planning models fail to consider renewable energy uncertainty methods, specifically concerning renewable energy confidence and future possible scenarios; thus, a confidence-based scenario cluster method is presented. A novel generator, network, load, and energy storage (GNLS) co-planning model is proposed in the paper. First, a confidence-based scenario cluster is built, which can reflect uncertainties by clustering and analyzing wind, solar, and load. Second, the proposed model focuses on load and energy storage co-planning, and in addition, relevant flexible indices are used to assess the model. Finally, the GNLS co-planning model is built as a bi-level stochastic model on continuous time scales. The model is solved using the Benders decomposition algorithm. The method in this paper is validated using an IEEE RTS 24-bus and a real test system in China to demonstrate the reduction in renewable energy curtailment and optimization of economic factors in power system planning.

Control-oriented thermal model and load identification for circulating cooling water system in precision process applications

With the increasing precision in machining and measurement, there is a growing demand for improved temperature stability in cooling water systems used in industrial processes. Accurate thermal models and load states are essential for developing efficient controllers to enhance temperature performance. This paper focuses on the development of thermal models for various components of circulating water systems in precision water-cooling processes. It presents a control-oriented thermal model framework that segregates the water circulation cycles and defines system inputs and processes. A novel identification algorithm is proposed to address thermal inertia and cyclic nonlinearity by extracting the cyclic period and cycle change rate. The algorithm can simultaneously estimate the state–space model and unmeasurable load disturbances. A validation experimental setup was constructed, and the results demonstrate that, for different flow scenarios, the estimated load and thermal model parameters align well, with correlations exceeding 0.85 and error ratios close to 10%. Additionally, the circulating water output temperature can be accurately predicted. The fitting degrees surpass 84% within five cycles, with correlations exceeding 0.97 and error standard deviations below 0.22 °C.

SIMPLIFIED SIMULATION MODEL OF LOAD IN A CLOSED PACKET SWITCHING NETWORK

An approach to simplified simulation modeling of packet switching network load has been developed. The simulated representation of network processes is based on a simplified mathematical model of the packet switching network, which is based on a discretized description of the load states of the network nodes and corresponds to the representation of the current state of the network in the tasks of managing its load. Changes in the node's filling state are modeled as a process of reproduction and death, and in the full load model, two factors of change are taken into account: the node's exchange of load with network users and transit load flow passing through it. To study an artificially selected "part of the network functioning process" - an approach to transit load modeling in a load-locked network is proposed. The approach allows for significant simplifications and ensures the leveling of the negative impact of simplifications on "load closure" (ensures the rule of constant amount of load in a closed network). The developed simulation model, firstly, creates the basis for the improvement of the complete model, and secondly, it is convenient for working out routing algorithms when analyzing them from the point of view of indicators of the ability to "influence" the load in the network. The obtained results are generalized, but attention is focused on the example of satellite packet switching networks.

Dynamic Response Study of Space Large-Span Structure under Stochastic Crowd-Loading Excitation

With the development of civil engineering, lightweight and high-strength materials, as well as large-span, low-frequency structural systems, are increasingly used. However, its self-oscillation frequency is often close to the stride frequency of pedestrians, which is easily affected by human activities. To study the effect of human activities on the dynamic response of structures, it is crucial to choose an appropriate anthropogenic load model. Considering the inter-subject and intra-subject variability of pedestrian walking parameters and induced forces in a crowd, we introduce the interaction rules between pedestrians based on the floor field cellular automata (FFCA). A stochastic crowd-loading model coupling walking parameters, induced forces between pedestrians, and induced forces between pedestrians and structures is proposed for simulating crowd-walking loads. The feasibility of the model is verified by comparing the measured response of a space large-span structure with the predicted response of the proposed stochastic crowd-loading model. The comfort level of the structure under different crowd densities was also evaluated based on the model. It was found that both random combinations of walking parameters and dynamic behaviors of pedestrians can cause significant differences in the structural response. Therefore, the crowd-loading model should consider the influence of pedestrian behavioral factors on the structural response.

Experimental study of dynamic pressure and wave load on variform vertical cylinders under extreme waves

Extreme waves pose a significant threat to the proliferating marine structures, however, the impact on the vertical cylinder with different cross-sectional shapes remains inadequately evaluated. Herein, we carried out a physical experiment, comprising 45 scenarios generated by three water depths, three wave paddle velocities, and five vertical cylinder models, to measure the extreme wave-induced pressure and load on this type of structure. The wave load and dynamic pressure distribution in time and spatial domains under the influence of cross-sectional shapes and wave conditions have been fully discussed. The experimental results indicate that: 1) As the position turns from front to back side, the circumferential pressure of five models initially decreases and then increases. 2) The maximum differential pressure between the front and back side decreases with increased water depth and decreased velocity, and occurs earlier than the peak pressure on the front side. 3) The chamfered cross-section (round and right triangle) can significantly reduce the wave load compared to the rectangular section, and the circular section suffers the lowest force logically. The dynamic pressure and wave load in this experiment can serve to establish a more sophisticated load model and provide valuable insights for marine structural design and disaster prevention.

Reliability-driven time-of-use tariffs for efficient plug-in electric vehicle integration

Demand response (DR) plays a crucial role in balancing electricity supply and demand, but existing studies on price-based DR for plug-in electric vehicle (PEV) load management lack comprehensive considerations. Therefore, this study designs reliability-driven time-of-use (TOU) tariffs for the integration of PEVs, considering various factors such as random component failures, the stochastic characteristics of non-dispatchable components, and fluctuations in load patterns and uncertainties. The proposed framework employs advanced stochastic simulation models to assess generation facility reliability amidst extensive PEV deployment in three steps. First, individual components, including conventional generation capacity, renewable energy sources, and demand, as well as PEV load models, are developed. Then, a system reserve margin assessment is carried out via the generation of seasonal synthetic time series data. During this step, innovative techniques, including box-plot methods and expert rules, are used to simplify the representation of the system reserve margin at each hour. Finally, optimized TOU pricing schedules for PEVs are generated. These pricing hours are initially categorized as off-peak, mid-peak, or on-peak, streamlining scenario analysis and aligning PEV charging profiles with predefined pricing schedules for grid reliability evaluation. Case studies have shown that the proposed method can improve the reliability indices by effectively mitigating the impacts.

Influence of Load Models and DG Operational Power Factor on Optimization of Shunt Capacitor Placement in Distribution Grids Considering Voltage Stability

The paper proposes a mathematical model of mixed-integer nonlinear programming (MINLP) to optimize the location and size of shunt capacitors in power distribution grids with distributed generation (DG), considering voltage stability constraints. At the same time, the paper also analyzes the influence of the load models, such as voltage-dependence load (ZIP load) and constant power load, together with DG’s operating power factor on the optimal solution. The objective function of the proposed optimization formulation is minimizing the total expenses, including the capital investment of capacitors and the expense incurred by network energy loss. This MINLP model includes constraints in the current and critical loading conditions, such as the system of power flow equations, nodal voltage limits, branch thermal limits, capacitor-related constraints, and restrictions of minimum security level. The proposed optimization model was evaluated on a modified IEEE 33-node distribution grid using the KNITRO commercial solver with the GAMS programming language. The calculation results show that the voltage stability constraints, load models, and operational power factor of the DG units have an essential influence on the optimal position and capacity of the shunt capacitors.

Time-dependent synchronization factor of crowd rhythmic motion and its application on intelligent structural monitoring

The synchronization factor is an index to evaluate the level of consistency for crowd motion under rhythmic guidance, which is important for crowd load modeling as well as structural vibration monitoring. Most of the existing synchronization factors were defined based on the time history of the crowd movement over a long period of time, failing to consider the time-dependent characteristics of intra-subject variability. Moreover, these factors were generally based on the data that can only be measured under laboratory conditions, making them difficult to be applied on the monitoring of structures subjected to crowd excitation in real engineering practice. In this regard, this paper proposed a novel time-dependent synchronization factor for a crowd in rhythmic motion. By using multiple object tracking technology, the head movements of each person in the crowd were measured as the basis for calculating the newly proposed time-dependent synchronization factor, which is defined as the ratio between a representative value of the crowd movement time history and the average of the same values for each person in the crowd. A series of experiments were organized to study the characteristics and the applicability of the synchronization factor, whose relation with structural responses was clearly observed in the laboratory experiments as well as in a real structure. The results demonstrated that the newly proposed time-dependent synchronization factor is effective when applied on the intelligent operation and maintenance of the engineering structures.

Theoretical and experimental investigation of vibration-assisted scratching silicon

Interaction between tip and workpiece plays a crucial role in determining the scratching depth in Vibration-assisted Tip Based Nanofabrication (VTBN), which is more complicated than that of conventional scratching (without vibration-assisted). To establish the relationship between the scratching depth and machining parameters, a cubecorner indenter is employed to conduct VTBN procedure. The indenter is simplified as a cone to calculate the contact model in both 1D groove and 2D surface machining processes. An instantaneous normal load model is established based on the developed tip-workpiece contact model. Due to the variation of instantaneous contact area, effective contact area is put forward for the first time to predict the normal load. Effects of vibration frequency and amplitude on the normal load and surface quality are analyzed based on the proposed model. Experimental results show that higher frequency and larger amplitude will reduce the effective contact area. Vibration can increase the scratching depth and width without enlarging the cutting force. Furthermore, the inconsistency caused by scratching directions in conventional scratching is also overcome during VTBN.

Advancing infrastructure resilience: machine learning-based prediction of bridges’ rating factors under autonomous truck platoons

AbstractThe operational characteristics of freight shipment will significantly change after the implementation of Autonomous and Connected Trucks (ACT). This change will have a significant impact on freight mobility, transportation safety, and the sustainability of infrastructure. Truck platooning is an emerging truck configuration that is expected to become operational in the future due to the rapid advancements in connected vehicle technology and autonomous driving assistance. The platooning configuration enables trucks to be connected with themselves and the surrounding infrastructure. This arrangement has shown to be a promising solution to improve the vehicles’ fuel efficiency, reduce carbon dioxide emission, reduce traffic congestion, and improve transportation service. However, platooning may accelerate the damage accumulation of pavement and bridge structures due to the formation of multiple load axles within each platoon since those structures were not designed for such loads. According to AASHTO, bridges are designed based on a notional live load model comprised of one or two trucks per lane in conjunction with or separate from an applied uniform load (AASHTO, LRFD 2022). This damage, if accumulated, its repair would require billions of dollars from the government and would impede the movement of both people and goods. The potential damage to infrastructure may arise due to various factors such as the number of trucks in a platoon, gap spacing between trucks, and the type of trucks. This research work includes a thorough parametric study with 295,200 computer simulations using SAP 2000. The goal was to evaluate the effect of different truck platooning configurations on the load rating of existing bridges. The obtained results served as the dataset for training various machine learning models, including Random Tree, Random Forest, Multi-Layer Perceptron (MLP), Support Vector Regression (SVR), K-Nearest Neighbor (KNN), and Extreme Gradient Boosting (XGBoost). Results showed that Random Forest model performed the best, with the lowest prediction errors. The proposed machine learning model has shown its effectiveness in identifying optimal platooning configurations for bridge structures within the scope of the study. Graphical Abstract

A Time-History Contact Force Model of the Dynamic Load of AERORail Structures

This study proposes two curves that depict the vehicle–bridge contact force in a novel transportation system named AERORail, which is a lightweight cable-supported structure in which the rails and the prestressed cable form the load bearing system. Based on the contact force identified from a full-scale AERORail system, single and double-valley curves were obtained as the idealized contact force model for large- and small-span AERORail systems, respectively. This was achieved by utilizing the Bezier curves and the least squares method. The proposed curves were verified through a moving load model from a previous study under various spans and speeds. Moreover, the structural response of the AERORail structure under high-speed vehicle passing was explored using the idealized contact force model. The simulation results show that the proposed contact force model can predict the displacement response of 5 m and 15 m spans with a relative error of less than 5%, proving that the model can be used for dynamic analysis of AERORail.

Enhancing riverine load prediction of anthropogenic pollutants: Harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models

Assessing riverine pollutant loads is a more realistic method for analysing point and non-point anthropogenic pollution sources throughout a watershed. This study compares numerous mathematical modelling strategies for estimating riverine loads based on the chosen water quality parameters: Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Suspended Solids (SS), and Ammoniacal Nitrogen (NH3–N). A riverine load model was developed by employing various input variables including river flow and pollutant concentration values collected at several monitoring sites. Among the mathematical modelling methods employed are artificial neural networks with feed-forward backpropagation algorithms and radial basis functions. The classical multiple linear regression (MLR) statistical model was used for the comparison. Four widely used statistical performance assessment metrics were adopted to evaluate the performance of the various developed models: the root mean square error (RMSE), mean absolute error (MAE), mean relative error (MRE), and coefficient of determination (R2). The considerable number of errors (with RMSE, MAE, and MRE) discovered in estimating riverine loads using the multiple linear regression (MLR) statistical model can be attributed to the nonlinear relationship between the independent variables (Q and Cx) and dependent variables (W). The feed-forward neural network model with a backpropagation algorithm and Bayesian regularisation training algorithm outperformed the radial basis neural network. This finding implies that, in addition to suspended sediment loads, riverine loads may be predicted using an artificial neural network using pollutant concentration (Cx) and river discharge (Q) as input variables. Other geographical and temporal fluctuation characteristics that may impact river water quality, on the other hand, may be incorporated as input variables to enhance riverine load prediction. Finally, riverine load analyses were successfully conducted to reduce the riverine load.