Proposed Integration Method Research Articles

Integration of STPA and TOPSIS fuzzy methods for risk analysis in aerospace projects

There are several types of risks in organisations and projects, including technological, financial, environmental, legal, and operational. This article focuses on a risk analysis framework for complex aerospace research projects, some of which are innovations in the area and do not have a history of data from previous activities. The objective of this study is to analyse the feasibility of integrating the systems theoretic process analysis (STPA) method for systemic assessment of safety and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) for prioritising unsafe control actions (UCAs). The proposed integration method was applied to the Laboratory of Injection Systems for Liquid Propellants at the Aeronautics Institute of Technology (ITA). The results obtained were the need for an emergency response plan, signalling, access control, and safety training for laboratory technicians. Therefore, risk analysis is essential to support the decision-making process, to identify and reduce hazards and losses.

An optimized method for extracting slope length in RUSLE from raster digital elevation

The Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE) have been widely used for predicting average soil loss. Slope length is an important topographical parameter of the L factor in USLE/RUSLE. Among the widely studied GIS procedures for extracting slope length, the distributed watershed erosion slope length (DWESL) based on the unit contributing area estimation method, which considers two-dimensional runoff process and cutoff factors, is a relatively complete model for calculating slope length. Slope length in the DWESL model is primarily calculated using conventional flow direction algorithms such as D8, Dinf, MS and MFD-md. However, DWESL outputs require further improvement due to the errors in the usual estimates of the uphill contributing area and the effective contour length of discrete elements. Combined with a theoretical differential equation of specific catchment area on hillsides, the calculation of the DWESL model was optimized without estimating the uphill contributing area or the effective contour length for each cell. The proposed integration method based on the topographical features slope line, contour curvature and cutoff factors (ITF method) was used to extract slope length from the raster digital elevation. Slope length extracted using the ITF method had the smallest error in verification of mathematical surfaces (average RRMSE = 0.0573), and its spatial distribution was more consistent with the structure of the terrain surface for all test data, relative to the conventional flow direction algorithms in the original DWESL model. The proposed ITF method could provide a reference for predicting soil erosion using the USLE/RUSLE model.

Integration of Interturn Fault Diagnosis and Torque Ripple Minimization Control for Direct-Torque-Controlled SPMSM Drive System

This article proposes an integration method for interturn fault diagnosis and torque ripple minimization control of direct-torque-controlled surface-mounted permanent magnet synchronous machine (SPMSM) drive system without requiring the specific fault severity (short-circuited turn ratio, current). In this method, the interturn fault is detected and located based on the amplitude and initial phase angle of the zero-sequence voltage component (ZSVC). Both the torque injection and the improved flux observer are applied to reduce the torque ripple caused by the interturn fault. Furthermore, the torque injection and the improved flux observer are directly calculated by using the already obtained amplitude and initial phase angle of the ZSVC during the fault diagnosis process, without requiring the specific values of short-circuited turn ratio and fault current. The experimental results validate the effectiveness of the proposed integration method for the direct-torque-controlled SPMSM drive system.

The proactive maintenance for the irreversible sulfation in lead-based energy storage systems with a novel resonance method

In this paper, the irreversible sulfation in lead acid battery (LAB) is essentially reconsidered as an electrical capacitive effect from an interdisciplinary perspective. A proactive maintenance concept based on the resonance method is first introduced to interpret the electrochemical processes of the irreversible sulfation for simultaneous diagnosis and restoration. The effectiveness of the restoration is verified by an average of 23% impedance decrease and an average of 8.6% capacity increase, which are consistent with the morphological change from a dense, tight connections to a coarsen, porous electrode surface. In terms of the diagnosis accuracy, the electrical capacitive effect is determined by measuring the break frequency of the LAB, where an 87.7% estimation accuracy is achieved compared to the analytical result from Nyquist curve. With the proposed integration method, it becomes possible to proactively maintain the LABs in lifecycle (separate service stages) non-invasively with both field convenience and electrochemical interpretation, which will act as a part of highly reliable, environment friendly and sustainable lead-based energy storage systems in the future.

Diagnosis of Friction on an Unbalanced Rotor by Phase-Shift Empirical Mode Decomposition Integration and Recurrence Plot

The friction and imbalance of components in rotating machines are some of the most recurrent failures that significantly increase vibration levels, thus affecting the reliability of the devices, the shelf life of its elements, and the quality of the product. There are many publications related to the different techniques for the diagnosis of friction and imbalance. In this paper, an alternative and new phase-shift empirical mode decomposition integration (PSEMDI) method is proposed to transform the acceleration into its velocity and displacement in order to construct the phase plane and recurrence plot (RP) and analyze the friction. The focus of PSEMDI and RP is to analyze nonlinear failures in mechanical systems. In machinery fault diagnosis, the main reason for using RP is to solve the integration of acceleration, and this can be achieved by phase-shifting the intrinsic mode function (IMF) with the empirical mode decomposition (EMD). Although the highest IMFs contain some frequencies, most of them have very few; thus, by applying the phase shift identity, the integration can be carried out maintaining the nonlinearities. The proposed method is compared with Simpson’s integration and detrending with the EMD method (here referred to as SDEMDI). The experimental RP results show that the proposed method gives significantly more information about the velocity and displacement spectra and it is more stable and proportional than the SDEMDI method. The results of the proposed integration method are compared with vibration measurements obtained with an interferometer.

Multi-Frame Integration Method for Radar Detection of Weak Moving Target

In this paper, we consider the multi-frame integration (including intra-frame integration and inter-frame integration) problem for the detection of weak moving targets, where range walk effect (RWE) occurs within the integration time. A novel integration method is proposed to achieve the accumulation of a target's multi-frame radar echoes. More specifically, the proposed integration method contains two main steps, where the modified Radon Fourier transform (RFT) is firstly used to realize the intra-frame coherent integration for every frame of echo signals. After that, the RFT-domain integration algorithm is presented to achieve the inter-frame coherent integration based on the characteristics of RFT outputs, during which the accumulation of target energy distributed in multiple frames could be realized. The explicit expressions and analysis for various performance measures of the proposed method, such as integration output response, probability of detection, input-output signal-to-noise ratio (SNR), and blind speed sidelobe (BSSL) response are derived and given. Simulation experiments are given to demonstrate the effectiveness of the proposed method.

A Non-Iterative Integration Scheme Enriching the Solution to the Coupled Maglev Vehicle–Bridge System

A non-iterative integration scheme is presented in this study to enrich the solutions to the coupled equations of the maglev vehicle–bridge system. The proposed integration scheme is composed of two integration methods aiming at providing the solutions to equation of motion and state-space equation. First, the equation of motion of the simply supported girder bridge is transformed by the modal superposition method. Then the state-space equation is used to describe the motions of both the vehicle and the suspension control system, with the associated matrices assembled using the fully computerized approach. By adopting this integration scheme, only pure vector calculations arise in the solution process, regardless of the existence of time-dependent displacement and velocity on the right-hand sides of the two coupled equations. The proposed integration method is of the second-order accuracy with and without damping. Being equipped with adequate numerical dissipation and dispersion, the method also possesses the characteristic of little computing errors, as can be achieved through the use of different pairs of parameters. Finally, numerical simulations have been conducted to assess the influence of different feedback gains, three types of bridges with different lengths, and guideway irregularity on the maglev vehicle–bridge system.

Non-Orthogonal Wireless Backhaul Design for Cell-Free Massive MIMO: An Integrated Computation and Communication Approach

In cell-free massive multiple-input-multiple-output system with wireless backhaul, the distributed access points (APs) and the center processing unit (CPU) are connected via wireless links. Hence, the limited backhaul bandwidth becomes a critical challenge to uplink transmission. To save the bandwidth while maintaining high transmission accuracy, we propose to deploy non-orthogonal transmissions in backhaul link and jointly optimize the detection computation mappings at the APs and the CPU under the non-orthogonal backhaul. First, we formulate the joint design problem subject to backhaul bandwidth constraint aiming at a better end-to-end transmission accuracy. Then, the non-trivial problem is parameterized and solved with a novel model-driven deep neural network, where wireless backhaul is integrated as a neural computing layer by exploiting the reciprocity between non-orthogonal transmission and additive operation. Evaluations show that, the proposed integration method outperforms the conventional approaches by a margin in both backhaul bandwidth cost and the symbol error rate.

An approach to evaluate non-point source pollution in an ungauged basin: a case study in Xiao'anxi River Basin, China

Abstract It is challenging to evaluate non-point source pollution (NPSP) quantitatively and comprehensively in a basin without gauged data. In this paper, the export coefficient model (ECM), source strength coefficient method (SSCM), and the equivalent pollution loading method (EPLM) were integrated to evaluate NPSP in the Xiao’anxi River Basin (XRB) in 2018. The results showed that NPSP is the primary pollution type in the study area for 68.1% of the total pollution load. The primary pollutant was total nitrogen (TN), which accounted for 56.16% of the total pollution. Moreover, rural residents' living sewage accounted for 48.81% of NPSP, which was the primary pollution source. The evaluation results are consistent with field investigation, which indicates that the proposed integration method is capable of NPSP assessment in an ungauged basin. In addition, the hydrological analogy method and Q–V linear fitting were used to determine the discharge and flow velocity to calculate water environmental capacity, and compare with the prediction of NPSP in the study area in 2022. It was found that the critical rehabilitation regions are Bachuan Town, Nancheng Town, and Er'ping Town. Furthermore, the primary pollutants, TN and total phosphorus (TP), exceeded the water environmental capacity by 76.67% and 48.58%, respectively.

Intelligent Time-Scale Operator-Splitting Integration for Chemical Reaction Systems.

The wide range of time scales in chemical reaction systems has become an important problem in reactive flow simulations. This work proposes an intelligent time-scale operator-splitting (OS) chemistry integration method, which is effective in reduction of numerical stiffness and model complexity. Different from most existing publications, a pretrained backpropagation neural network is used to identify the slow and fast reactions and detect the sources of model stiffness on the fly, which replaces the expensive eigendecomposition of Jacobian matrix. With the fast-slow decomposition, the chemical source term can be represented as the sum of a stiff part and a nonstiff part. A stable time-scale OS integration is performed to solve the stiff chemical ordinary differential equations, which balances the computational cost with accuracy. In the simulation, a favorable comparison of the proposed integration method with the existing ODE solvers, such as implicit Euler, explicit Euler, and Runge-Kutta, is included to show its effectiveness and merits.

A modified soil water content measurement technique using actively heated fiber optic sensor

Abstract Soil water content measurement is critical in practical engineering. The actively heated fiber Bragg grating optic sensor (FBGS) has great potential of multi-point measurement for soil water content measurement in field. In this study, the effect of heating time on the measurement accuracy is discussed, and modifications are made for actively heated fiber optic (AHFO) sensors. The results demonstrate that if an integration data analysis method is used, the accuracy and reliability of soil water content measurement with AHFO sensors will be improved. Both a short fiber length and a short-term heating pattern are effective and can help to reduce soil disturbance. With the proposed integration method, a short heating time is guaranteed for measuring the soil water content. Such improvements will reduce the thermal disturbance to soil sample and improve the reliability of measurement.

The recovery of waste heat from the absorber vent gases of a CO2 capture unit by using membrane distillation technology for freshwater production

In this study, direct contact membrane distillation (DCMD) technology was proposed to produce freshwater by utilizing the low-grade waste heat from the gases purged from the absorber of a CO2 capture unit. A Rate-based model has been used to simulate a monoethanolamine (MEA)-based CO2 capture process in Aspen Plus® V.10, and DCMD unit was simulated with the MATLAB software. The regeneration energy requirement in the CO2 capture process and freshwater production in DCMD unit were analyzed by varying the operating parameters. Cold seawater and purged gas were allowed to pass through the additional heat exchanger; as a result, the temperature of seawater increased. Then the warmed seawater was injected into the DCMD unit to produce freshwater. The freshwater production was 88,599 L/day at the feed temperature of 52.2 °C, which reduced to 85,050 L/day when the feed temperature declined to 50.3 °C. The freshwater production was 88,950 L/day at the permeate temperature of 10 °C, which declined to 78,450 L/day when the permeate temperature increased to 20 °C. Since adequate amount of freshwater was produced by the proposed system, the proposed integration method could help to mitigate environmental pollution and freshwater crises.

Multi-Event Modeling and Recognition Using Extended Petri Nets

This paper addresses the event modeling and recognition problem in video surveillance systems using the system net on the Petri Net (PN) formalism. The single event on the foundation of prior knowledge is first modeled via arranging event schemes from the design document. Then, finite sequential runs (FSRs) determined by semantic features in training clips drive elements of the proposed single event model. Finally, the multi-event model is built automatically from single event models via a proposed integration method using multi-level features (including high-level semantic features and low-level features like numerical characters of individual trajectories). We provide a novel solution to event conflict issue through an extended system net where the resultant event type is determined by the decision tree technique. The comparison between the proposed methodology and other approaches in the literature is reported via experiments on an acknowledged public dataset.

Reusing the Evaluations of Basis Functions in the Integration for Isogeometric Analysis

We propose a new approach to reuse the basis function evaluations in the numerical integration of isogeometric analysis. The concept of reusability of the basis functions is introduced according to their symmetrical, translational and proportional features on both the coarse and refined levels. Based on these features and the parametric domain regularity of each basis, we classify the bases on the original level and then reuse them on the refined level, which can reduce the time for basis calculations at integration nodes. By using the sum factorization method and the mean value theorem for the integrals, a new integration method with high integral efficiency is proposed. We validate the proposed method by some structural analysis problems in domains with different dimensionality. Comparing the numerical result accuracy and the time cost of the proposed integration method with the full Gauss integration quadrature, it turns out to be very promising.

A Two-Stage Buck–Boost Integrated LLC Converter With Extended ZVS Range and Reduced Conduction Loss for High-Frequency and High-Efficiency Applications

Two-stage cascade architecture is widely used in the modular power supply applications. In order to reduce the additional component number caused by the cascading structure, the power switch integration technique is proposed in numerous literature studies. However, the power switch integration leads to both the efficiency degradation and the abnormal gain of the stage employed. In this article, the four-switch noninverting buck–boost converter is merged with the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> resonant converter. The proposed integration method has no awful influence on the efficiency and the gain of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> stage. Meanwhile, the soft switch capability of the integrated bridge can be enhanced due to the accumulation of the two currents of the buck–boost stage and the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> stage during dead time. Moreover, the current of the two-stage will commutate to cancel out with each other during the conduction period, reducing the conduction loss and improving the overall efficiency. The benefits of the integrated bridge make the proposed converter appropriate for the high-frequency and high-efficiency application. Finally, a 720-W 1-MHz prototype is built to prove the performance of the proposed converter. The prototype achieves a peak efficiency of 96.4% and the input voltage range of 250–420 V.

A New Wireless EV Charging System With Integrated DC–DC Magnetic Element

A dc–dc conversion stage is commonly used for a wireless electric vehicle (EV) battery charging system. The dc–dc stage requires a bulky inductor to charge the battery either in constant voltage (CV) or constant current (CC) modes. In this article, a new magnetic structure for the wireless EV charging system is proposed to integrate the dc–dc inductor with the receiver coil on the vehicle side. The proposed structure utilizes the existing core material in the wireless power circuit pads and provides a more compact design and an efficient wireless charger system for EV applications. The proposed magnetic structure is modeled in 3-D, and the finite-element analysis (FEA) results are presented and compared with measurements. Moreover, the effect of the proposed integration method on the wireless charging system performance is investigated, and the results are presented. A 3.3-kW/85-kHz wireless charger is optimally designed and built to evaluate the proposed configuration. Furthermore, the efficiency and the output voltage of the wireless charging system are also measured and compared with the simulation results. The simulation and experimental results show the performance of the proposed structure.

Galileo Ionospheric Correction Algorithm: An Optimization Study of NeQuick‐G

AbstractAt present most low‐cost GNSS receivers operate one frequency in the L band. For them one of the largest error contributions is the delay of radio signals in the Ionosphere. NeQuick‐G is the official ionospheric correction algorithm (ICA), which has been adopted for Galileo, the European GNSS Programme. The NeQuick‐G implementation is complex when compared with other ICAs. It is also demanding in terms of computational resources. The Joint Research Centre completed a reference implementation of NeQuick‐G based on the official document “Ionospheric Correction Algorithm for Galileo Single Frequency Users” provided by the European Global Navigation Satellite Systems Agency. The rationale behind the JRC implementation of NeQuick‐G was the intent to write an independent source code from scratch, without using the pseudo‐codes from the reference document and solely relying on the physics descriptions. Using such implementation as baseline, this paper describes an optimization attempt of the official pseudo‐code from an algorithmic perspective. The objective was to reduce the computational load while not sacrificing the performance. The new proposed integration method is able to speed up calculations to 21% and 49% with respect the two official integration algorithms. The overall computational burden depends on the number of operations, which is eventually closely correlated to the number of calls of the ionospheric model. This underlines the quest to find an integration method reducing this number of calls. Moreover, based on the findings of this study, the authors strongly recommend revisiting the convergence control of the integration routines introduced in (European Commission, 2016, https://www.gsc‐europa.eu/sites/default/files/sites/all/files/Galileo_Ionospheric_Model.pdf).

Rao‐Blackwellised particle filtering for low‐cost encoder/INS/GNSS integrated vehicle navigation with wheel slipping

This study presents a Rao-Blackwellised particle filter (RBPF)-based encoder/inertial navigation system (INS)/global navigation satellite system (GNSS) integration method for improving the navigation performance of an autonomous land vehicle (ALV) with wheel slipping. In contrast to traditional integration methods, the proposed integration method introduces an overall wheel slip consideration for the ALV, which greatly improves the accuracy of the velocity estimation, especially when the inertial sensor is low cost. Additionally, the proposed integrated system uses double-difference pseudorange measurements instead of single point positioning results provided by low-cost GNSS receivers, which greatly improves the accuracy of the position estimation. To verify the navigation performance of the proposed integrated system, comparisons between the states estimated by the proposed system, the EKF-based integrated system and the joint wheel-slip and motion-estimation system are provided. The results of the experiment show that the proposed integrated system has the highest accuracy in both the position estimation and the velocity estimation among the three compared systems, and can improve the navigation performance during GNSS signals outages.

A quasi-consistent integration method for efficient meshfree analysis of Helmholtz problems with plane wave basis functions

A quasi-consistent integration method is presented for the efficient meshfree analysis of Helmholtz problems. The plane wave basis functions are employed for the reproducing kernel meshfree approximation to accurately represent the acoustic field resulting from Helmholtz problems. In order to improve the computational efficiency of Galerkin meshfree analysis of Helmholtz problems, a reproducing kernel gradient smoothing approach is introduced into the meshfree formulation with plane wave basis functions. In the proposed method, the smoothed gradients of meshfree shape functions with plane wave basis functions are built upon a reproducing kernel gradient representation and the integration consistency of Galerkin meshfree formulation is implicitly ensured. Furthermore, a quasi-consistent integration scheme is proposed to compute the smoothed gradients, which aims to balance the efficiency and accuracy for meshfree analysis of Helmholtz problems. The proposed integration method leads to fully consistent integration when one wave direction is considered, and nearly consistent integration if two wave directions are taken into account, where the boundary sample points of integration cells are particularly preferred since they are simultaneously used by neighboring integration cells with efficiency gain. Numerical results demonstrate that the proposed methodology is much more efficient and accurate for Galerkin meshfree analysis of Helmholtz problems, in comparison with the standard meshfree formulations using high order Gauss quadrature rules.

An Integration Optimization Method for Power Collection Systems of Offshore Wind Farms

The traditional power collection system design separately optimizes the connection topology and the cable cross sections, which may result in the inherent shortcoming of lacking the most economical solutions. In this pursuit, the present work envisages the development of an integrated design method for general wind farm power collection systems, which integrated the coupling random fork tree coding, union-find set loop identification, current and voltage drop calculation models, and a high performance optimization algorithm. The proposed coupling random fork tree coding, for the first time, realized the coupling code of the substation location, connection topology, and cable cross sections, providing the basis for the integration design of the power collection system. The optimization results for discrete and regular wind farms indicated that the proposed integration method achieved the best match of topology, substation location, and the cable cross sections, thus presenting the most economical scheme of the power collection system. Compared to the traditional two-step methods, the integration method used more branches while acquiring them, to maintain the lower number of wind turbines in each branch. Furthermore, it also employed large cross-section cables to reduce the energy loss caused by the impedance in the topology, thereby resulting in a slight increased cable cost; however, the total cost was minimized. The proposed method is very versatile and suitable for the optimization of power collection systems containing any number of wind turbines and substations, and can be combined with any evolutionary algorithm.