Actual Capacity Research Articles

An encoder-decoder fusion battery life prediction method based on Gaussian process regression and improvement

The prediction ability of all traditional machine learning models is limited to a few batteries. When the RUL of more batteries needs to be predicted, the prediction performance of traditional machine learning is not very good. For long-term battery capacity prediction, it is obtained in a recursive way. However, adding the predicted value to the input sequence will cause a large cumulative error after multiple recursive predictions. Based on the codec model, this paper introduces Gaussian process regression, which is used in multi-step prediction to improve the codec fusion method and the Savitzky-Golay method is utilized to smooth the training set. A new kernel function was designed to further improve the accuracy. The method of dynamic weights is adopted to minimize accumulated error. The experimental results show that the fusion prediction method can reduce the cumulative error of recursive prediction without losing the declining trend of the actual capacity of the battery, and can predict the RUL of zinc-ion batteries more precisely than other models.

Method of Vertiport Capacity Assessment Based on Queuing Theory of Unmanned Aerial Vehicles

Urban air traffic has gradually attracted attention in recent years, which will bring endless vitality to future urban development. An objective and accurate method of assessing vertiport capacity is the basis for the air traffic flow management of UAVs, which plays an important role in improving the efficiency of urban airspace resources. First of all, this paper establishes a theoretical capacity calculation model for ground facilities such as takeoff and landing platforms, taxiways and aprons, respectively. Next, this paper analyzes the service characteristics of each ground facility and establishes different types of UAV queuing systems to obtain UAV delay curves based on a UAV Poisson flow arrival model. Subsequently, a suitable acceptable delay level is selected to obtain the corresponding UAV flow, which means the actual capacity of UAV operations. Eventually, the validity of the model is verified through actual drone data arithmetic examples. The calculation results show that the combination of “1 landing + 2 takeoffs” can achieve better capacity results and that the landing platform is more prone to congestion than the takeoff platform. Change in average service time has the greatest impact on the apron capacity, and the takeoff platform is the most sensitive to changes in the acceptable delay level.

Application of matrix multiplication in signal sensor image perception

Abstract LOT wireless sensor nodes are limited by physical factors, usually have weak computing power and endurance, and wireless communication methods are very vulnerable to information theft. Therefore, it is of great significance to ensure the safe and efficient transmission of images in new application scenarios. In view of the need for an efficient image transmission, this paper combines compressed sensing technology with p-tensor product theory, applies the above theory to distributed wireless sensor networks, and uses the correlation of adjacent sensor nodes in wireless sensor networks to propose an improved a joint sparse model for measurement matrices and reduction algorithms. The feasibility is verified by simulation experiments, and the comparison between joint reconstruction and single reconstruction, and the application of various algorithms in other algorithms is carried out, and the actual completion time and storage capacity are analysed. The minimum completion time for wavelet transform is 1.29, the sparse estimated time for the selection of preliminary P waves is 0.07 and the compressed sensing time is 0.20. The maximum completion time for wavelet transform was 1.32, for sparse estimation, it is 0.62, for preliminary P-wave selection, it is 0.17, and for compressed sensing, it is 0.88. The processing time is no >3 s and the runtime is only 0.22–0.88 s. The results show that compared with the compressed sensing of a single node, the joint sparse model based on distributed compressed sensing has a smaller reconstruction error, and can achieve high-precision signal reconstruction when the measurement value is small.

Разработка автоматизированного алгоритма для расчета пропускной способности железнодорожной линии

Purpose: To develop an automated algorithm using simulation modeling tools that allows calculating actual capacity of railway line with mixed traffic. Analytical formulas underlie the algorithm. Results: The algorithm features the use of simulation modeling tools and taking into account of the same name coefficient. The application of the given software product will allow to raise the efficiency and accuracy of actual capacity calculation accuracy. The data, obtained during the simulation, were compared to the data in the timetable, their discrepancy was revealed which basis on, simulation modeling value, integrated into existing formulas, was found. Based on all calculations, software algorithm has been developed with its subsequent implementation in Maple software environment in order to automate calculations and increase their efficiency. Methods: Simulation modeling and analytical comparison method were used. Practical significance: Improving the accuracy of calculations of the values of available capacity on the network of JSC "Russian Railways" and simplifying the implementation of such calculations. This algorithm, if implemented, would bring the calculated values closer to the real ones.

Real-time control of combined sewer systems: Risks associated with uncertainties

Model Predictive Control (MPC) of combined sewer systems can reduce environmental degradation caused by uncontrolled overflows. However, practical uncertainties are often neglected when assessing the potential of MPC strategies. This paper aims to understand the risks associated with using a non-perfect internal MPC-model, real precipitation forecast, and realistic dynamic system capacity fluctuations. An MPC with the objective to reduce the total combined sewer overflow (CSO) volume was implemented in the case study of Eindhoven in the Netherlands where highly sensitive waterways receive the sewer overflows. Two types of risks were identified: relative system performance loss and operative deterioration. The former entails a practical decrease in efficacy of controlling CSO spills compared to the theoretical situation, whereas the latter describes the aggravation of environmental pollution compared to a static form of system operation. The results obtained demonstrate that precipitation forecast uncertainty is associated with a small relative system performance loss. Opposite to this, significant performance loss was observed as a consequence of uncertainties in the internal MPC model and the actual sewer system capacity available. The latter caused additional combined sewer overflows compared to a statically optimised control for smaller precipitation events.

Extracellular Matrix-Based Approaches in Cardiac Regeneration: Challenges and Opportunities.

Cardiac development is characterized by the active proliferation of different cardiac cell types, in particular cardiomyocytes and endothelial cells, that eventually build the beating heart. In mammals, these cells lose their regenerative potential early after birth, representing a major obstacle to our current capacity to restore the myocardial structure and function after an injury. Increasing evidence indicates that the cardiac extracellular matrix (ECM) actively regulates and orchestrates the proliferation, differentiation, and migration of cardiac cells within the heart, and that any change in either the composition of the ECM or its mechanical properties ultimately affect the behavior of these cells throughout one's life. Thus, understanding the role of ECMs' proteins and related signaling pathways on cardiac cell proliferation is essential to develop effective strategies fostering the regeneration of a damaged heart. This review provides an overview of the components of the ECM and its mechanical properties, whose function in cardiac regeneration has been elucidated, with a major focus on the strengths and weaknesses of the experimental models so far exploited to demonstrate the actual pro-regenerative capacity of the components of the ECM and to translate this knowledge into new therapies.

Strategies for Minimizing Charging Time in Commercial Nickel-Rich/Silicon-Graphite Lithium-Ion Batteries

The emerging nickel-rich/silicon-graphite lithium-ion technology is showing a notable increase in the specific energy, a main requirement for portable devices and electric vehicles. These applications also demand short charging times, while actual charging methods for this technology imply long time or a significant reduction in cycling life. This study analyses the factors that affect the charge behavior for 18,650 commercial nickel-rich/silicon-graphite batteries. For that, long-term cycling tests have been carried out, including electric vehicle standard tests. It can be concluded that this technology has two key issues to develop an efficient charge method: high charge rates should be avoided, mainly below 15% state of charge, and the charge should be finished at 95% of actual cell capacity. This allows that, regardless of application and cell degradation level, cells can be recharged in 2 h without a negative impact on cycling life. For faster charge applications, a new method has been developed to minimize charging time without compromising the cycle life as much as the high current manufacturer method. The proposed fast charge method has proven to be notably faster, recharging in an average 1.3 h (48% less than the high current method and 68% less than the standard method).

Adsorbed and free gas occurrence characteristics and controlling factors of deep shales in the southern Sichuan Basin, China

Deep shale gas (3500–4500 m) will be the important succeeding field for the growth of shale gas production in China. Under the condition of high temperature and high pressure in deep shale gas reservoirs, its gas occurrence characteristics are markedly different from those of medium and shallow layers. To elucidate the gas occurrence characteristics and controlling factors of deep shales in the Wufeng-Longmaxi Formation, methane adsorption, low-temperature N2, and CO2 adsorption experiments were conducted. The results show that in deep shales, the mesopores provide approximately 75% of the total specific surface area (SSA) and 90% of the total pore volume (PV). Based on two hypotheses and comparing the theoretical and actual adsorption capacity, it is speculated that methane is adsorbed in deep shale in the form of micropore filling, and free gas is mainly stored in the mesopores. Correlation analysis demonstrated that TOC is the key material constraint for the adsorption capacity of deep shale, and micropore SSA is the key spatial constraint. Other minerals and mesopore parameters have limited effect on the amount of adsorbed gas. Moreover, the free gas content ranges from 2.72 m3/t to 6.20 m3/t, with an average value of 4.60 m3/t, and the free gas content ratio is approximately 58%, suggesting that the deep shale gas reservoirs are dominated by free gas. This ratio may also increase to approximately 70% when considering the formation temperature effect on adsorbed gas. Gas density, porosity, and gas saturation are the main controlling factors of free gas content, resulting in significantly larger free gas content in deep shale than in shallower formations.

THỰC TRẠNG DẠY HỌC THEO HƯỚNG TIẾP CẬN STEAM Ở CẤP TIỂU HỌC TẠI VIỆT NAM TRONG GIAI ĐOẠN HIỆN NAY

Many scientists have conducted research on the contents and methods of organizing STEAM education at all levels, including primary education. Besides studying the theoretical system, it is now necessary to conduct in-depth research on the current state of STEAM education application. The article focuses on surveying the current situation of applying STEAM education to the learning activities of primary school students in Vietnam. Research results reflect the actual capacity of teachers and students in implementing STEAM activities, pointing out the causes affecting the effectiveness of activities, and contributing to the creation of a STEAM educational culture in primary education. learn. On that basis, the author offers some solutions to overcome the limitations of applying STEAM education in the survey area.

An improved thermal single particle model and parameter estimation for high-capacity battery cell

Single particle model (SPM) is an electrochemical model which can be used with energy balance to calculate the state of charge, terminal voltage, and temperature of the battery. The conventional SPM neglects the lithium-ion dynamics in the electrolyte, and the energy balance usually does not consider the heat transfer delay from the battery center to the surface. These lead to model errors when SPM is used for high-capacity battery cells. In this study, we propose several strategies to improve the model accuracy for high-capacity battery cells. First, the actual discharge capacity is considered by modifying the desired Li-ion flux at the electrode surface. Second, a part of the equivalent circuit model is integrated with SPM to consider the resistance in the electrolyte computationally efficiently. Third, the delay in the heat transfer from the center to the surface is represented using a second-order system dynamic. In electric vehicles, battery cells are stacked as a pack; we account for the additional heat generated by stacking pressure-induced swelling repression. Finally, parameter estimation is conducted to determine the best parameter values of the model using the experimental data. The reference values are set using a dimensionless scale-up approach. When the parameters are estimated and the model is tested with the validation data, the error percentages in the calculated terminal voltage and temperature are smaller than 2.0410% and 3.5032%, respectively, even with the cell variances.

A Machine Learning Architecture Replacing Heavy Instrumented Laboratory Tests: In Application to the Pullout Capacity of Geosynthetic Reinforced Soils.

For economical and sustainable benefits, conventional retaining walls are being replaced by geosynthetic reinforced soil (GRS). However, for safety and quality assurance purposes, prior tests of pullout capacities of these materials need to be performed. Conventionally, these tests are conducted in a laboratory with heavy instruments. These tests are time-consuming, require hard labor, are prone to error, and are expensive as a special pullout machine is required to perform the tests and acquire the data by using a lot of sensors and data loggers. This paper proposes a data-driven machine learning architecture (MLA) to predict the pullout capacity of GRS in a diverse environment. The results from MLA are compared with actual laboratory pullout capacity tests. Various input variables are considered for training and testing the neural network. These input parameters include the soil physical conditions based on water content and external loading applied. The soil used is a locally available weathered granite soil. The input data included normal stress, soil saturation, displacement, and soil unit weight whereas the output data contains information about the pullout strength. The data used was obtained from an actual pullout capacity test performed in the laboratory. The laboratory test is performed according to American Society for Testing and Materials (ASTM) standard D 6706-01 with little modification. This research shows that by using machine learning, the same pullout resistance of a geosynthetic reinforced soil can be achieved as in laboratory testing, thus saving a lot of time, effort, and money. Feedforward backpropagation neural networks with a different number of neurons, algorithms, and hidden layers have been examined. The comparison of the Bayesian regularization learning algorithm with two hidden layers and 12 neurons each showed the minimum mean square error (MSE) of 3.02 × 10-5 for both training and testing. The maximum coefficient of regression (R) for the testing set is 0.999 and the training set is 0.999 for the prediction interval of 99%.

Performance of Planting Tools (Seed Planter) on Rice Land, Palu City, Central Sulawesi

The application of innovation and technology in agricultural machinery in the world is one of the factors in increasing production and productivity of agricultural products. One of them is the application of agricultural machinery, namely the process of planting on agricultural land. The use of agricultural machinery at the farm level, especially planting, is still rarely carried out, as long as the availability of agricultural labor is decreasing. Most agricultural workers have entered non-productive age, while the interest of the younger generation to enter the world of agriculture is getting lower, especially conventional agriculture. Agricultural mechanization can solve this problem. The purpose of this research is to produce the performance of the seed planter in lowland rice fields. The research method uses an agrotechnical study that measures the theoretical capacity (Kt), actual working capacity (Ka), the efficiency of the seed planter's performance, and wheel slip on the seed planter. Based on the test results the average field capacity performance is 1.301 ha/hour, the test results are the actual average field capacity 0.650 ha/hour, the test results are the average efficiency of the tool performance is 50.0%, and the average slip test results wheel that is 13.75%. Factors that affect the performance test of planting tools, among others: operator skills, soil conditions, wheel slip, shape and size of planting tools, as well as the topography of a land.
 Keywords: Actual Work Capacity (Ka), Theoretical Work Capacity (Kt), Efficiency, Wheel Slip, Seed Planter

A Reliable Anti-Interference Probe Based on Fluorescence Intensity Ratio Technique for Cryogenic Temperature Detection

In this paper, a reliable anti-interference probe based on fluorescence intensity ratio technique is proposed for cryogenic temperature detection in refrigeration process, the sensing unit of which is based on a self-made coreless tellurite optical fiber (TOF) co-doped with Er <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3+</sup> /Yb <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3+</sup> ions. The temperature information was demodulated by analyzing the fluorescence spectral changes. In order to meet the needs of practical applications, the dual-curing method was applied to realize the TOF splicing, and the thin-walled silica tube was used to provide robust packaging. For the first time, the anti-cross-sensitive properties of the fluorescent probe under vibration and liquid interference were quantified, and the repeated response deviation was on the order of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−5</sup> . The actual working capacity of the probe was experimentally investigated by applying it to measuring the circulating exhale and cryogenic equipment, in which a fast time response of about 2.11 s and a small absolute error of 0.80 K were obtained. The probe has good stability and repeatability, and can work stably even in complex environments with vibrations and liquids, showing strong anti-interference ability. In addition, the robust package and easy method make the probe suitable for mass fabrication.

ANALISIS SIMPANG TIGA BERSINYAL TUGU ADIPURA KOTA PAYAKUMBUH MENGGUNAKAN METODE MKJI 1997

AbstractThe rapid growth in the number of vehicles each year is not accompanied by an increase in road infrastructure. The population of Payakumbuh which is increasing from year to year causes the need for transportation equipment to increase. 36,960 vehicles and cars pass through the streets of Payakumbuh every day. Of the 36,960 vehicles, 70% were two-wheelers and 30% were four-wheelers. Comparing road conditions and transportation facilities will cause traffic congestion, especially during peak hours, and will have an impact on increasing pollution, travel time, costs, social and actual working time. The actual capacity of all intersections is 4106 pcu/hour, the degree of saturation of all intersections can be DS = 0.25 &lt; 0.6 so the road category is smooth. The delay time for all these intersections is Dtot = 4.66 sec/pcu and the highest queue probability at all intersections is 13.61% Keywords: Signalized intersections, road lanes, intersection performance, queuing opportunities, degree of saturation, intersection capacity

CZM-based FE numerical study on pull-out performance of adhesive bonded-in-rod (BiR) joints for timber structures

Bonded-in-Rod (BiR) connections for timber structures are becoming rather popular solution, in place of other traditional fastening techniques. Besides, design rules and recommendations in support of safe and robust verification are still poor in existing standards. As such, the actual mechanical performance and load-bearing capacity – which is severely affected by a multitude of operational parameters – should be possibly addressed with the support of experimental investigations. In this paper, a Cohesive Zone Modelling (CZM) based, Finite Element (FE) numerical investigation is proposed for a total of 144 BiR joints characterized by various geometrical and mechanical properties, including grain orientation (α = 0° or 90°), adhesive type (polyurethane or epoxy glue), diameter (d = 10, 14, 20 mm) and anchorage length of rods (L = 60, 100, 200, 400 mm) is presented. Most importantly, the attention is also focused on the analysis of service class effects / moisture content (9, 18 or 27 %) on the actual residual capacity of the examined joints, which is of paramount importance for safe design applications in timber structures. Based on validation of input model properties to past experimental results, the sensitivity of basic mechanical performance indicators for the examined BiR samples is discussed in the paper.

Follow the Crowd with Uncertain Service Capacity

Problem definition: Customer joining behavior is of major concern for service systems where the service capacity is uncertain. Academic/practical relevance: It remains unclear whether customer inference of uncertain service capacity can lead to follow the crowd (FTC) behavior. Management can release capacity information, but how it affects system performance needs to be understood. Methodology: We use a single-server queue to analyze the joining behavior of customers who infer the actual service capacity based on the queue length upon arrival. We also characterize the impact of capacity information disclosure both analytically and numerically. Results: We find that when other customers’ tendency to join the service increases, a tagged customer can make more accurate inferences of service capacity based on queue length. This inference effect arises together with the congestion effect and can lead to FTC when it outweighs the latter. When multiple equilibria exist, we characterize the conditions under which the inference effect is significant at the aggregate customer level so that the joining equilibrium with a larger joining threshold is Pareto-optimal. Managerial implications: Management needs to be careful in setting the information disclosure policy, as the key problem parameters may affect its impact on system throughput and social welfare in opposite directions. Funding: L. Yang was supported by the National Natural Science Foundation of China [Grants 71991461 and 71532006]. W. Shang was supported by the Hong Kong Research Grants Council [GRF Project LU 13502219]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.1139 .

Unequal access to justice: an evaluation of RSPO’s capacity to resolve palm oil conflicts in Indonesia

In 2009 the Roundtable on Sustainable Palm Oil (RSPO) established a conflict resolution mechanism to help rural communities address their grievances against palm oil companies that are RSPO members. This article presents the broadest ever comprehensive assessment of the use and effectiveness of the RSPO conflict resolution mechanism, providing both overviews and in-depth analysis. Our central question is: to what extent does the RSPO conflict resolution mechanism offer an accessible, fair and effective tool for communities in Indonesia to resolve conflicts with companies? Our aim is not only to provide a ‘reality check’ of this mechanism but also to contribute to the wider debate on how communities can seek access to justice when engaged in intractable conflicts with palm oil companies. For data collection, we took three steps. First, we used our own database of 150 conflicts between communities and companies in Indonesia. We identified 64 conflicts that involved RSPO member companies, of which 17 prompted communities to convey their grievances to the RSPO’s conflict resolution mechanism. Second, we used the database of the RSPO, which handled 85 complaints against companies in Indonesia in the period 2009–2020. Third, we conducted fieldwork, in total, about 6 months of fieldwork and extensive interviews on three conflicts involving RSPO companies to identify mechanisms leading to (and reasons for) both failed and successful instances of conflict resolution. For our assessment, we used three criteria to assess the conflict resolution mechanism of the RSPO: accessibility, procedural justice, and the outcomes of the process. We conclude that—on all counts—the conflict resolution mechanism is biased in favor of companies. The result of these biases is that the actual capacity of the RSPO’s mechanism to provide a meaningful remedy for rural communities’ grievances remains very limited. This unequal access to justice sustains conflicts between companies and communities over land.

Study of SOC Estimation by the Ampere-Hour Integral Method with Capacity Correction Based on LSTM

The estimation of the state of charge (SOC) of a battery’s power is one of the key technologies in a battery management system (BMS). As a common SOC estimation method, the traditional ampere-hour integral method regards the actual capacity of the battery, which is constantly changed by the usage conditions and environment, as a constant for calculation, which may cause errors in the results of SOC estimation. Considering the above problems, this paper proposes an improved ampere-hour integral method based on the Long Short-Term Memory (LSTM) network model. The LSTM network model is used to obtain the actual battery capacity variation, replacing the fixed value of battery capacity in the traditional ampere-hour integral method and optimizing the traditional ampere-hour integral method to improve the accuracy of the SOC estimation method. The experimental results show that the errors of the results obtained by the improved ampere-hour integral method for the SOC estimation are all less than 10%, which proves that the proposed design method is feasible and effective.

Reinforced Concrete Corbels Shear Test: The Triangular-Truss Method Evaluation

In this paper, five reinforced concrete double-corbel specimens with the same designed bearing capacity are produced according to the triangular-truss method (TTM) in GB 50010-2010. Corbels with different dimensions and reinforcement configurations are obtained by separately varying the concrete compressive strength and shear span. The differences in the mechanical performance and load-bearing capacity of the corbels are compared to evaluate the accuracy and rationality of the TTM under specific variables. Then, the accuracy in predicting the load-bearing capacity of GB 50010-2010, ACI 318-19, EC 2, CSA A23.3-04, the softened strut-and-tie method, and the Russo strut-and-tie method is compared. The results show that the safety factor (ratio of the actual bearing capacity to the designed bearing capacity) of the TTM is increased from 1.419 to 1.718 when the concrete strength is improved from 20.8 MPa to 65.3 MPa; the safety factor of the TTM is increased from 1.414 to 1.859 when the shear span–depth ratio is increased from 0.25 to 0.67. Compared to GB 50010-2010, ACI 318-19, and EC 2, the predictions of CSA A23.3-04 for corbels are closer to the test values. The safety level of codes GB 50010-2010, ACI 318-19, and EC 2 is essentially the same; both the SSTM and the Russo STM are accurate in the predictions.

Considerations on efficient procedural steps for seismic capacity assessment and diagnostics of historic structural glass systems

Structural designers are nowadays supported by standards and guidelines to optimize the mechanical performance and safety level of glass load-bearing elements and assemblies in buildings. Key role is given to deformation and stress check, and post-breakage verification, for newly designed glass systems. Performance limits are provided also for extreme events, such as earthquakes. Besides, major risk for people could derive from existing/historic glass components and systems that have not been conceived to offer minimum structural capacity against operational loads and accidents. No technical recommendations are available to quantify their actual vulnerability and capacity, thus retrofits and mitigations are also hard to plan. In this paper, possible procedural methodology steps towards are addressed. The attention is given to present technical guidelines for structural design, on one side, and on the optimized use of non-destructive methods (like Operational Modal Analysis (OMA)) and numerical methods to facilitate diagnostic steps and the mechanical characterization of components, as well as to realistic description of boundaries and even damage. Practical examples are discussed for a case-study glass-steel envelope built in 60s in Italy, which is analyzed with the support of Finite Element (FE) numerical models against in-plane and out-of-plane seismic actions.