Local Scheme Research Articles

Anti-seepage measures for the upper reservoir of one pumped-storage power station

Abstract Seepage control plays an important role in the design of pumped storage power station. In this paper, the seepage characteristics and geological conditions of the upper reservoir of a pumped storage power station are analyzed, and the natural seepage of the upper reservoir is calculated. According to the characteristics and amount of leakage, the upper reservoir can be controlled by local seepage control scheme, and the anti-seepage treatment scheme of the south reservoir bank is compared and analyzed. After the local anti-seepage treatment of upper reservoir, the daily seepage volume decreased from 5585m3/d to 2304m3/d, which indicates that the selected anti-seepage scheme is suitable. This paper can provide useful reference for similar projects in the future.

Inverse Hessian by stochastic projection and application to system identification in nonlinear mechanics of solids

Parameter identification in nonlinear mechanics of solids, a class of non-convex optimization problems of significant interest, often has to balance fast convergence with enhanced exploration. Local optimization schemes based on Newton or quasi-Newton updates cannot tread this fine balance. A similar limitation also applies to many derivative-free global evolutionary searches that typically end up with slower convergence. Notwithstanding a relatively rapid convergence around a local optimum, schemes using classical gradients require that the objective function be smooth. Thus, applied to real-world scenarios, these algorithms face challenges such as non-smoothness including discontinuities in the objective function and costly evaluations of gradients or Hessians, whenever possible. Based on a novel stochastic projection to estimate inverse Hessians, this work aims at generalizing a fast Newton-type local search whilst retaining capabilities of noise-assisted exploration in non-convex optimization. In principle, such a meeting of the best of both worlds in optimization should provide for a powerful paradigm shift, offering a versatile and robust tool for solving complex identification and variational problems arising in nonlinear mechanics of solids. The approach is well-suited even for cases where the objective function is implicitly defined and not amenable to explicit evaluation. In a first implementation of our proposal, we assess its performance against a few benchmark non-convex problems. Finally, we solve a parameter estimation problem for an isotropic and incompressible hyperelastic material.

Research on Aerodynamic Performance Optimization and Drag Reduction of mid-sized SUV on CFD

With the increase of vehicle ownership, the environment and energy issues are highlighted, and reducing vehicle wind resistance has become the key to improving fuel economy. Based on the theory of fluid mechanics and project development experience, this paper develops a medium-sized SUV model for wind resistance reduction. Through the simulation modeling of the vehicle's external flow field, the proportion model wind tunnel test and the optimization scheme research of the exterior shape, the bottom of the vehicle and the engine room, the wind resistance is significantly reduced. Combined with the wind tunnel test results, the actual contribution of each local optimization scheme is verified, and the EGO algorithm is used for further optimization to further reduce the wind resistance coefficient. This paper summarizes the key parts and regularity experience of the aerodynamic drag reduction of the medium-sized SUV model, providing guidance for the development of high-precision vehicle performance in the future. The research methods and results of this paper are of great significance for improving the aerodynamic performance and fuel economy of vehicles.

Extending a dry‐environment convection parameterization to couple with moist turbulence and a baseline evaluation in the GRIST model

AbstractThis study presents an extension of a dry‐environment convection scheme (Tiedtke–Bechtold) to couple with a boundary‐layer moist turbulence scheme. The deep and shallow convective updraught is modified to develop in a moist environment and the large‐scale budget of cloud condensate takes account of the influence of compensation subsidence. An ambiguous layer is introduced in the sub‐cloud layer transport of shallow convection to mimic the non‐local transport that is ignored in the moist local turbulence scheme. Long‐term global simulation suggests that the modified convection and moist turbulence improve low cloud and short‐wave cloud radiative forcing. This includes a more realistic climatological structure of stratocumulus‐to‐cumulus transition and ameliorated biases in liquid water path. For short to mid‐term hindcasts in June 2021, the modified convection coupled with moist turbulence mitigates some regional over‐forecasts of precipitation. They improve the forecast ability for light and moderate precipitation. The modified model still retains the capability to capture the diurnal features of continental rainfall.

Location-Aware Range-Error Correction for Improved UWB Localization.

In this paper, we present a novel localization scheme, location-aware ranging correction (LARC), to correct ranging estimates from ultra wideband (UWB) signals. Existing solutions to calculate ranging corrections rely solely on channel information features (e.g., signal energy, maximum amplitude, estimated range). We propose to incorporate a preliminary location estimate into a localization chain, such that location-based features can be calculated as inputs to a range-error prediction model. This way, we can add information to range-only measurements without relying on additional hardware such as an inertial measurement unit (IMU). This improves performance and reduces overfitting behavior. We demonstrate our LARC method using an open-access measurement dataset with distances up to 20 m, using a simple regression model that can run purely on the CPU in real-time. The inclusion of the proposed features for range-error mitigation decreases the ranging error 90th percentile (P90) by 58% to 15 cm (compared to the uncorrected range error), for an unseen trajectory. The 2D localization P90 error is improved by 21% to 18 cm. We show the robustness of our approach by comparing results to a changed environment, where metallic objects have been moved around the room. In this modified environment, we obtain a 56% better P90 ranging performance of 16 cm. The 2D localization P90 error improves as much as for the unchanged environment, by 17% to 18 cm, showing the robustness of our method. This method evolved from the first-ranking solution of the 2021 and 2022 International Conference on Indoor Position and Indoor Navigation (IPIN) Competition.

Deficit Irrigation Effects on Cotton Growth Cycle and Preliminary Optimization of Irrigation Strategies in Arid Environment.

With the changing global climate, drought stress will pose a considerable challenge to the sustainable development of agriculture in arid regions. The objective of this study was to explore the resistance and water demand of cotton plants to water stress during the flowering and boll setting stage. The experimental plot was in Huaxing Farm of Changji city. The plots were irrigated, respectively, at 100% (as the control), 90%, 85% and 80% of the general irrigation amount in the local area. The relationship between the various measured indexes and final yield under different deficit irrigation (DI) treatments was studied. The results showed that deficit irrigation impacted the growth and development processes of cotton during the flowering and boll setting stage. There was a high negative correlation (R2 > 0.95) between the maximum leaf area index and yield. Similarly, there was a high correlation between malondialdehyde content and yield. Meanwhile, 90% of the local cotton irrigation contributed to water saving and even increasing cotton yield. Furthermore, based on the results, the study made an initial optimization to the local irrigation scheme by utilizing the DSSAT model. It was found that changing the irrigation interval to 12 days during the stage could further enhance cotton yield and conserve resources.

Wind power and the cost of local compensation schemes: A Swedish revenue sharing policy simulation

Local resistance towards wind power is a central challenge for the energy transition, implying that legally imposed compensation schemes for nearby residents may become prevalent in the near future. I use GIS-coded data on detached residential buildings in Sweden to simulate a variety of revenue sharing schemes applied to every present and planned commercial scale wind power project, focusing on documenting the impact on investor costs. I compare models that entitle compensation for distances between six and ten times the tip height of the closest turbine, imposing schemes that are both constant within the eligible distance, as well as declining with the distance from the turbine. When compensations are awarded for residents as far away as ten times the turbine height, foregone revenues exceed two percent for one-fourth of the projects in the southern region even under the declining model, indicating that the scheme could have a substantive effect on the localization decisions of future investments.

Triple‐indexed passive islanding detection strategy for grid‐connected distributed generation networks using an extended Kalman filter

AbstractIslanding detection is a challenging issue in modern grid‐connected distributed generation networks (GCDGN). Generally, islanding detection has two categories local and remote, local schemes can be categorized into active, passive, and hybrid schemes. This article proposes a triple‐indexed passive islanding detection (TIPID) scheme using an extended Kalman filter (EKF). Initially, the EKF algorithm is applied on voltage signal at the point of the common coupling to estimate the desired fundamental and non‐fundamental features. The first index, known as the cumulative voltage logarithmic index, is computed by taking the natural logarithm of the fundamental voltage features to detect any variations in the GCDGN. The second index, known as the voltage differentiation index (VDI), is calculated from the fundamental voltage features, while the third index, known as the odd‐order harmonic distortion index (OOHDI), is obtained from the non‐fundamental odd‐order harmonics of the PCC voltage. Then, the VDI and OOHDI are compared to pre‐defined threshold to detect/distinguish islanding events. The proposed TIPID method is validated through extensive simulations on the IEEE 13‐bus test bed via MATLAB/Simulink 2022b. Results show that under both balanced/unbalanced load & generation, the proposed TIPID approach detects islanding occurrences with reduced non‐detection zone (NDZ) in less than 5 ms.

Determination of vancomycin and meropenem in serum and synovial fluid of patients with prosthetic joint infections using UPLC-MS/MS.

Numerous studies have suggested that intra-articular administration of antibiotics following primary revision surgery may be one of the methods for treating prosthetic joint infection (PJI). Vancomycin and meropenem are the two most commonly used antibiotics for local application. Determining the concentrations of vancomycin and meropenem in the serum and synovial fluid of patients with PJI plays a significant role in further optimizing local medication schemes and effectively eradicating biofilm infections. This study aimed to establish a rapid, sensitive, and accurate ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for determining the concentrations of vancomycin and meropenem in human serum and synovial fluid. Serum samples were processed using acetonitrile precipitation of proteins and dichloromethane extraction, while synovial fluid samples were diluted before analysis. Chromatographic separation was achieved in 6min on a Waters Acquity UPLC BEH C18 column, with the mobile phase consisting of 0.1% formic acid in water (solvent A) and acetonitrile (solvent B). Quantification was carried out using a Waters XEVO TQD triple quadrupole mass spectrometer with an electrospray ionization (ESI) source in positive ion mode. The multiple reaction monitoring (MRM) mode was employed to detect the following quantifier ion transitions: 717.95-99.97 (norvancomycin), 725.90-100.04 (vancomycin), 384.16-67.99 (meropenem). The method validation conformed to the guidelines of the FDA and the Chinese Pharmacopoeia. The method demonstrated good linearity within the range of 0.5-50 μg/ml for serum and 0.5-100 μg/ml for synovial fluid. Selectivity, intra-day and inter-day precision and accuracy, extraction recovery, matrix effect, and stability validation results all met the required standards. This method has been successfully applied in the pharmacokinetic/pharmacodynamic (PK/PD) studies of patients with PJI.

Biophysical Drivers of Seasonal Hysteresis of Urban Heat Islands Across Climates and Urban Landscapes

AbstractThe phenomenon of seasonal hysteresis between urban heat islands (UHIs) and background surface temperature was reported in many studies, but a unifying explanation for the causes of its magnitude, shape and looping direction remained less clear, and the impacts of urban landscapes and background climate on such hysteresis were also the subject of enquiry. Here we performed a systematic study based on a long‐term offline simulation for surface energy budgets, surface air and skin temperature of the urban‐biosphere system in East China. It was carried out with an up‐to‐date land surface model — the CLM5‐LCZs (the Community Land Model version 5 (CLM5) coupled with a newly developed urban canopy model representing diverse urban landscapes with the local climate zones classification scheme). To isolate the causes of UHIs hysteresis, a simplified framework was constructed by combining a mathematical representation of grid/subgrid model outputs, the two‐resistance mechanism method and the time‐lagged cross correlation analysis. The results exhibited distinct hysteresis patterns of UHIs such as twisted, concave‐down, concave‐up and convex‐up curve across diverse background climates and urban landscapes. The basic shapes of hysteresis depict a gradual transition from concave/convex‐up to concave/convex‐down by characterized by a larger winter UHIs from a wetter and warmer climate to a drier and colder climate. Magnitude and seasonality of surface UHIs are separately dominated by the urban‐rural contrast of evapotranspiration and heat storage at daytime and nighttime, whereas across‐climate variations of daytime and nighttime surface UHIs hysteresis are regulated by the phase shift of convection efficiency and anthropogenic heat. Urban landscapes affect the hysteresis mainly by altering the amplitude rather than the shape of looping curves. Our work could provide a fuller picture of how to mitigate urban warming considering inter‐seasonal tradeoffs over a broader region.

MA-VLAD: a fine-grained local feature aggregation scheme for action recognition

MA-VLAD: a fine-grained local feature aggregation scheme for action recognition

Analysis and performance evaluation of computation models for node localization in deep sea using UWSN

SummaryUnderwater wireless sensor network (UWSN) connects the real world to the hidden resources available deep into the sea using sensor nodes deployed sparsely and are interconnected to gather information for any movement/change in the ocean. The computed information on nodes obtained from concurrently running UWSN's applications will be meaningful, only if the location of this change will be identified. Nevertheless, it is always difficult to obtain the exact location coordinates of any misadventure like tectonic plate's movement but using localization algorithms in UWSN helps to obtain the coordinates. Since localization algorithms for terrestrial networks are not feasible for UWSN because of environmental challenges. Moreover, GPS systems do not work after 15 m of depth and the radio frequency gets suppressed. So, the requirement arises to analyze existing localization approaches in the deep sea where acoustic signals are used for communication and data transfer. In this paper, along with describing the UWSN's applications and challenges, the underwater localization schemes are reviewed to present, summarize, and mention the scope of improvement. Further, classification into range‐based and range‐free categories of these schemes is depicted with implementation in the NS2.30 simulation environment of some of the recent techniques to showcase the reasons for better performance.

Vertical Localization for Strongly Coupled Data Assimilation: Experiments in a Global Coupled Atmosphere‐Ocean Model

AbstractStrongly coupled data assimilation allows observations of one Earth system component (e.g., the ocean) to directly update another component (e.g., the atmosphere). The majority of the information transfer in strongly coupled atmosphere‐ocean systems is passed through vertical correlations between atmospheric boundary layer and ocean mixed layer fields. In this work we use correlations from a global, coupled model to study vertical observation‐space localization techniques for strongly coupled data assimilation. We generate target correlations using a bootstrapping approach from a single 24 hr forecast from a realistic global, weakly coupled atmosphere‐ocean cycling system with an 80‐member ensemble, which is the ensemble size currently used by the NOAA operational global data assimilation system. We compare data assimilation methods with different localization schemes using single‐update, offline experiments. We develop a new strategy for optimal observation space localization, called Empirical Optimal R‐localization (EORL), to give an upper bound on the improvement we can expect with any localization scheme. We then evaluate Gaspari‐Cohn localization, which is a commonly used parametric localization function and review its performance with respect to the optimal localization scheme. We investigate how the performance of these localization strategies changes with increasing ensemble sizes. Our results show that strongly coupled data assimilation has the potential to be an improvement over weakly coupled data assimilation when large ensembles are used. We also show that the Gaspari‐Cohn localization function does not appear to be a particularly good choice for cross‐fluid vertical localization.

Novel design of a personnel protection system for large particle accelerators: balancing safety, reliability, and cost

As the primary safety protection system for particle accelerators, the Personnel Protection System (PPS) not only prioritizes safety but also recognizes the importance of system reliability to ensure the stable operation of the accelerator and foster trust among system stakeholders. When designing the PPS, a distinction can be made between critical safety functions and common functions. There are at least three critical safety functions: firstly, ensuring that personnel are prohibited from accessing the tunnel during accelerator operation; secondly, preventing accelerator activation in the presence of personnel within the tunnel; and thirdly, enabling prompt termination of accelerator operations during emergency situations. To meet the demanding safety integrity level requirement of SIL3, multiple layers of defense and safety redundancy are employed. In order to mitigate the potential risks arising from human errors, significant emphasis is placed on improving the automation and intelligence of the system. This research focuses on the development of a comprehensive novel system that incorporates multiple defense mechanisms to meet the stringent safety and reliability demands of large particle accelerators represented by High Energy Proton Source (HEPS). It designs novel local optimization schemes, including the semi-redundant control system, zero-count interlock, intelligent search and secure, and electromagnetic control key, among others. These pioneering approaches are seamlessly integrated into the comprehensive system, effectively enhancing its capabilities and overall efficiency. Furthermore, this study conducts an analysis of the reliability of interlocking equipment, employing measures such as hierarchical DC power, parallel redundancy, and optimized signal processing to enhance its overall reliability. Finally, a method for determining the Safety Integrity Level (SIL) and assessing the reliability of PPS is developed, and the system's performance is validated.

Accelerated Benders decomposition and local branching for dynamic maximum covering location problems

The maximum covering location problem (MCLP) is a key problem in facility location, with many applications and variants. One such variant is the dynamic (or multi-period) MCLP, which considers the installation of facilities across multiple time periods. To the best of our knowledge, no exact solution method has been proposed to tackle large-scale instances of this problem. To that end, in this work, we expand upon the current state-of-the-art branch-and-Benders-cut solution method in the static case, by exploring several acceleration techniques. Additionally, we propose a specialised local branching scheme which exploits the separability of the problem by time period. This scheme uses a novel distance metric in its definition of subproblems and features a new method for efficient and exact solving of the subproblems. These methods are then compared through extensive computational experiments, highlighting the strengths of the proposed methodologies.

LVI-Fusion: A Robust Lidar-Visual-Inertial SLAM Scheme

With the development of simultaneous positioning and mapping technology in the field of automatic driving, the current simultaneous localization and mapping scheme is no longer limited to a single sensor and is developing in the direction of multi-sensor fusion to enhance the robustness and accuracy. In this study, a localization and mapping scheme named LVI-fusion based on multi-sensor fusion of camera, lidar and IMU is proposed. Different sensors have different data acquisition frequencies. To solve the problem of time inconsistency in heterogeneous sensor data tight coupling, the time alignment module is used to align the time stamp between the lidar, camera and IMU. The image segmentation algorithm is used to segment the dynamic target of the image and extract the static key points. At the same time, the optical flow tracking based on the static key points are carried out and a robust feature point depth recovery model is proposed to realize the robust estimation of feature point depth. Finally, lidar constraint factor, IMU pre-integral constraint factor and visual constraint factor together construct the error equation that is processed with a sliding window-based optimization module. Experimental results show that the proposed algorithm has competitive accuracy and robustness.

LF3PFL: A Practical Privacy-Preserving Federated Learning Algorithm Based on Local Federalization Scheme.

In the realm of federated learning (FL), the exchange of model data may inadvertently expose sensitive information of participants, leading to significant privacy concerns. Existing FL privacy-preserving techniques, such as differential privacy (DP) and secure multi-party computing (SMC), though offering viable solutions, face practical challenges including reduced performance and complex implementations. To overcome these hurdles, we propose a novel and pragmatic approach to privacy preservation in FL by employing localized federated updates (LF3PFL) aimed at enhancing the protection of participant data. Furthermore, this research refines the approach by incorporating cross-entropy optimization, carefully fine-tuning measurement, and improving information loss during the model training phase to enhance both model efficacy and data confidentiality. Our approach is theoretically supported and empirically validated through extensive simulations on three public datasets: CIFAR-10, Shakespeare, and MNIST. We evaluate its effectiveness by comparing training accuracy and privacy protection against state-of-the-art techniques. Our experiments, which involve five distinct local models (Simple-CNN, ModerateCNN, Lenet, VGG9, and Resnet18), provide a comprehensive assessment across a variety of scenarios. The results clearly demonstrate that LF3PFL not only maintains competitive training accuracies but also significantly improves privacy preservation, surpassing existing methods in practical applications. This balance between privacy and performance underscores the potential of localized federated updates as a key component in future FL privacy strategies, offering a scalable and effective solution to one of the most pressing challenges in FL.

A parallel multi-resolution Smoothed Particle Hydrodynamics model with local time stepping

Smoothed Particle Hydrodynamics (SPH) model has exhibited remarkable efficacy in addressing strongly nonlinear large deformation problems. However, the expensive computational cost could limit its application. To address this, we propose a novel parallel multi-resolution SPH model with a local time step strategy. This model integrates the multi-resolution model with a Message Passing Interface-based parallelization framework, wherein subdomains discretize the computational domain at varying resolutions. Meanwhile, a local fourth-order Runge-Kutta time integration scheme is introduced, enabling different subdomains to use different time steps. Subdomains of varying resolutions are devoid of overlapping regions, and changes in particle resolution at interfaces are achieved through a dynamic strategy involving particle merging and splitting. Besides that, we conducted a comparative analysis of different SPH discretization formats concerning their impact on the accuracy of multi-resolution particle discretization. Finally, several numerical tests were conducted to validate the accuracy and efficiency of the present multi-resolution SPH model.

High Accuracy Localization Scheme Using 1-Bit Side Information: Achievability from a GDoP Perspective

In this paper, we provide a novel methodology for high-precision positioning that utilizes 1-bit additional information, which applies to various positioning techniques. The proposed approach leverages binary information to indicate if a user is within a specified space of interest and refines the estimated location information outside this area. By matching the estimated locations outside the area of interest with the valid location information within, this methodology corrects the positional data obtained through any arbitrary positioning technique, aligning the estimated positions with the intended spatial boundaries. Performance analysis metrics, such as Average Positioning Error (APE) and Cumulative Distribution Function for positioning coverage, were employed to assess the effectiveness of the proposed methods. Numerical simulations demonstrate how the proposed method enhances the averaged positioning accuracy, significantly outperforming the conventional time of arrival method. Furthermore, the proposed positioning correction methodology demonstrates validated feasibility applicable to an arbitrary existing positioning method.

A Local Line Optimization Model for Urban Rail Considering Passenger Flow Allocation

It is important to strengthen the research on urban rail transit (URT) existing line renovation strategies. In this paper, we investigate the optimization of bottlenecks that are less attractive but have strong travel demand in existing URT networks. A URT local line optimization model is constructed. The maximum passenger flow and minimum project cost are chosen as the optimization objective for the benefit of both passengers and operators, and several actual constraints are considered in the proposed model, such as the station interval. In order to obtain higher computational efficiency and accuracy, a passenger flow allocation method is embedded in a genetic algorithm with elitist preservation. Taking the local network of the Beijing URT as a case study, the calculation results show that the designed algorithm can quickly and effectively obtain the optimal solution, and the generated local line scheme is able not only to meet the regional travel demand, but also to optimize the connection relationship of the existing URT network. This study can provide a reference method for increasing the attraction of URT and optimization of existing URT networks.