Minimum Rate Research Articles

Early enteral nutrition support for patients with acute pancreatitis in the inpatient setting: a best practice implementation project.

Acute pancreatitis is a major disease that endangers the health and lives of people. Historically, clinical therapy has recommended. that patients with acute pancreatitis remain nil by mouth. As one of the therapies recommended in recent guidelines, early enteral nutrition support reduces the incidence of infectious complications and reduces the risk of severe conditions. However, early enteral nutrition support has not been optimally implemented within clinical practice for acute pancreatitis inpatients. This evidence implementation project aimed to increase compliance with best practice recommendations for early enteral nutrition support, while standardizing the enteral nutrition support process and reducing the incidence of delayed enteral nutrition. The project was guided by the JBI Evidence Implementation Framework, which is grounded in the audit and feedback process, as well as a seven-stage structured approach to identifying and managing barriers to compliance with recommended practices. In the baseline audit, compliance rates were low for all evidence-based audit criteria. Four of the eight criteria showed 0% compliance. However, after implementation, all eight criteria achieved a minimum compliance rate of 60%, with Site 2 achieving 90% to 100% compliance. In addition, nurses improved their knowledge and skills in early enteral nutrition support. The incidence of delayed enteral nutrition also fell from 86.2% to 20.7% at both study sites. The implementation strategy included a training program, psychological interventions, and financial and human resource support. This project not only significantly improved early enteral nutrition support for acute pancreatitis patients, but also increased nurses' knowledge and practice skills, standardized the process of enteral nutrition support, and reduced the incidence of delayed enteral nutrition. http://links.lww.com/IJEBH/A177.

Efficient disease identification using symptom-based ensemble models and bayes-search optimization

Symptom-based disease identification is crucial to the diagnosis of the disease at the early stage. Usage of traditional stacking and blending models i.e., with default values of the models cannot handle the multi-classification data properly. Some of the existing researchers also implemented tuning with the help of a grid search approach but it consumes more time because it checks all the possible combinations. Suppose if the model has n estimators with k values it needs to check (n*k)! elements combination, this makes the learning time high. The proposed model chooses the estimators to train the model with in a considerable amount of time using an advanced tuning technique known as “Bayes-Search” on an ensemble random forest and traditional, support vector machine. The advantage of this model is its capability to store the best evaluation metrics from the previous model and utilise them to store the new model. This model chooses the values of the estimator based on the probability of selection, which reduces the elements in search space i.e., (< (n-k)!). The proposed model defines the objective function with a minimum error rate and predicts the error rate with the selected estimators for different distributions. The model depending on the predicted value decides whether to store the value or to return the value to the optimizer. The Bayes search optimization has achieved +9.21% accuracy than the grid search approach. Among the two approaches random forest has achieved good accuracy and less loss using Bayes search with cross-validation.

The complex circuitry of interactions determining coexistence among plants and mycorrhizal fungi.

We present a mechanistic model of coexistence among a mycorrhizal fungus and one or two plant species that compete for a single nutrient. Plant-fungal coexistence is more likely if the fungus is better at extracting the environmental nutrient than the plant and the fungus acquires carbon from the plant above a minimum rate. When they coexist, their interaction can shift from mutualistic to parasitic at high nutrient availability. The fungus is a second nutrient source for plants and can promote the coexistence of two plant competitors if one is better at environmental nutrient extraction and the other is better at acquiring the nutrient from the fungus. Because it extracts carbon from both plants, the fungus also serves as a conduit of apparent competition between the plants. Consequently, the plant with the lower environmental nutrient extraction rate can drive the plant with the higher environmental nutrient extraction rate extinct at high carbon supply rates. This model illustrates mechanisms to explain several observed patterns, including shifts in plant-mycorrhizal growth responses and coexistence along nutrient gradients, equivocal results among experiments testing the effect of mycorrhizal fungi on plant diversity, and differences in plant diversity among ecosystems dominated by different mycorrhizal groups.

Comparative study of copper nanoparticles over radially stretching sheet with water and silicone oil

Abstract Copper nanoparticles are widely used in many sectors and research endeavors owing to their unique properties, including a large surface area, catalytic capabilities, and high thermal and electrical conductivity. The selection of the base fluid for copper nanoparticles should be contingent upon the anticipated application requirements since various fluids exhibit distinct characteristics that could potentially impact the mobility of the nanoparticles. The present investigation analyzes heat transfer phenomena occurring across a radially stretched surface. The research explores the effects of different states of Cu nanoparticles when combined with base fluids, such as water and silicone oil, on the heat transfer process. The momentum and energy equations are transformed into nonlinear ordinary differential equations by applying the similarity transformation. The boundary value problem-fourth-order (BVP4C) method numerically solves the governing ordinary differential equation for the modeled problem. In addition, the influence of various factors such as the slip parameter, solid volume fraction, Eckert number, Prandtl number, and unsteadiness parameter are examined. It has been discovered that blade-shaped nanoparticles transfer heat as quickly as possible via silicone oil and water. However, for platelet-shaped nanoparticles, a minimum heat transfer rate has been noted. The maximum skin friction coefficient is observed in platelet-shaped nanoparticles, while blade-shaped nanoparticles have the lowest skin friction coefficient.

Design of signage guidance system for tourist attractions based on computer vision technology

In order to improve tourists’ sense of touring experience, this research proposes a signage navigation system for mobile scenic spots. Firstly, the system uses a recurrent neural network algorithm incorporating convolutional neural network for image recognition function to obtain relevant information through image recognition. Then the target localization of the image is performed according to the single-stage target detection algorithm, and the location of the landscape in which the user is located is localized by the recognized image information. The results show that the algorithm can achieve 86.7% recognition accuracy, and it can recognize part of the image samples when the recognition time reaches the range of 0.8 min–1 min. The single-stage target detection algorithm has a localization accuracy of 97.2% with a minimum loss rate of 1.1%. And the algorithm has high average accuracy and full class average accuracy values. The system has good application value.

Unlocking the potential of oncology biomarkers: advancements in clinical theranostics.

Cancer biomarkers have revolutionized the field of oncology by providing valuable insights into tumor changes and aiding in screening, diagnosis, prognosis, treatment prediction, and risk assessment. The emergence of "omic" technologies has enabled biomarkers to become reliable and accurate predictors of outcomes during cancer treatment. In this review, we highlight the clinical utility of biomarkers in cancer identification and motivate researchers to establish a personalized/precision approach in oncology. By extending a multidisciplinary technology-based approach, biomarkers offer an alternative to traditional techniques, fulfilling the goal of cancer therapeutics to find a needle in a haystack. We target different forms of cancer to establish a dynamic role of biomarkers in understanding the spectrum of malignancies and their biochemical and molecular characterization, emphasizing their prospective contribution to cancer screening. Biomarkers offer a promising avenue for the early detection of human cancers and the exploration of novel technologies to predict disease severity, facilitating maximum survival and minimum mortality rates. This review provides a comprehensive overview of the potential of biomarkers in oncology and highlights their prospects in advancing cancer diagnosis and treatment.

Eccentric binaries: Periastron events and tidal heating

Binary stars cannot be fully understood without assessing the interaction effects between the two components and the impact of these effects on observational diagnostics. Periastron brightening events, also known as the heartbeat phenomenon, are a clear manifestation of this type of interaction. We aim to explore the role of tidal shear energy dissipation in stars undergoing periastron brightening events. We performed a computation from first principles that uses a quasi-hydrodynamic Lagrangian scheme to simultaneously solve the orbital motion and the equations of motion of a 3D grid of volume elements covering the inner, rigidly rotating "core" of a rotating, the tidally perturbed star. The equations of motion include the gravitational acceleration of both stars, the centrifugal, Coriolis, gas pressure accelerations, and viscous coupling between volume elements. The method is illustrated for a grid of model binary systems with a 10 M$_ primary that is perturbed by a 6.97 M$_ companion in eccentric orbits ($e$=0 - 0.7). The model was then applied to the heartbeat star MACHO We find an increase by factors sim 10$^ $ in tidal shear energy dissipation at periastron, consistent with the majority of observed heartbeat stars. The magnitude of the periastron effect correlates with the degree of departure from synchronicity: stars rotating much faster or much slower than the synchronous rate at periastron present the strongest effect. We confirm that for eccentricities leq 0.3, pseudo-synchronization occurs for 0.8$< ave <$1, where $ ave $ is the average orbital angular velocity. The minimum energy rotation rate (pseudo-synchronism) for $e$=0.5 and 0.7 occurs for 1.0$< ave <$1.15. The tidal shear energy dissipation model reproduces from first principles the sim 23<!PCT!> maximum brightness enhancement at periastron of MACHO 80.7443.1718. Our results suggest that the magnitude and shape of the heartbeat signal may serve as diagnostics for the internal stellar rotation and turbulent viscosity values.

Determination of the minimum soil infiltration rate of sunken green space considering the annual runoff collection ratio, sunken depth and sunken green space area of Hefei city, China.

Sunken green space is one of the urban rainwater collection facilities, which belongs to Low Impact Development (LID) techniques. It plays a key role in the construction of sponge city, and the amount of runoff collection is usually affected by the area of the sunken green space, the infiltration rate of the soil, and the annual runoff collection rate. To determine the minimum soil infiltration rate of sunken green space considering the annual runoff collection ratio of sponge cities, this paper selects a residential district in Hefei city, China, as the case study. Based on 45 years of precipitation data, the designed rainfall corresponding to annual runoff collection ratios of 75%, 80% and 85% is 21.3 mm, 23.4 mm and 27.5 mm, respectively. The characteristics of rainfall infiltration in sunken green space are analyzed by using the water balance model and runoff yield and conflux model. The results reveal that the soil infiltration rate is 1.16×10-4 cm/s~3.88×10-3 cm/s when the sunken depth is 0.1 m~0.3 m and that the ratio of green space area is 5%~25%. The runoff collection of the reconstructed sunken green space is 2.87 times and 1.98 times that of the nonsunken green space and the nonreconstructed sunken green space, respectively. That is to say, under the comprehensive performance of the sunken depth, sunken green space area, the steady soil infiltration rater of the reconstructed sunken green space cannot be less than the value obtained in this paper. Otherwise, the requirements of annual total runoff reduction ratio of the sponge city cannot be met. Therefore, this study provides references for realizing the ratio of annual runoff collection and sponge city construction in similar urban areas. It can also be applied to optimal selection of sunken green space in some sponge city projects.

Recording of suspected adverse drug reaction reporting in veterinary free-text clinical narratives.

To use text mining approaches to identify instances of suspected adverse drug reactions recorded in first opinion veterinary free-text clinical narratives, and to evaluate whether these were also reported to either the Veterinary Medicines Directorate or the relevant Marketing Authorisation holder in order to derive an estimate of the suspected adverse drug reaction (sADR) minimum under-reporting rate. To characterise sADR reports and explore whether particular features are associated with report submission. Two regular expressions were developed to identify mentions of "adverse drug reactions" and "side effects" in the free-text clinical narratives of electronic health records contained within the Small Animal Veterinary Surveillance Network database. Consultations containing a match for the developed regular expressions were manually reviewed for inclusion and further classified to determine the suspected product, seriousness and expectedness of the event, and an indication of whether the event had been reported. The associations between event characteristics and reporting were explored using Fisher's exact tests. A total of 10,565 records were manually reviewed from which 827 sADRs were identified. Approximately 90% of these sADRs were not recorded as reported. Suspected adverse drug reactions that were not considered "expected" were recorded as reported more frequently than "expected" sADRs. However, clinical severity did not appear to impact on whether there was a record of reporting. This is the first estimate of under reporting sADRs based on real world evidence from veterinary clinical records. The under-reporting rate implied by this study highlights that further interventions are required to improve reporting rate within the veterinary profession in order to support pharmacovigilance activities and improve drug safety.

Radioprotection issues in uraniferous minerals collections with reference to an actual case.

Our work investigated the radioprotection implications associated with the possession of a collection of uraniferous minerals. Considering different scenarios, we developed (and applied to an actual collection) specific formulas for radiation doses evaluation. We discussed the shielding necessary to reduce the gamma irradiation down to the required values. A mathematical model was developed to estimate the minimum air flow rate to reduce the radon air concentration below the reference values. The radiation risks associated to the handling of single specimens was also addressed, including hand skin irradiation and shielding capabilities of surgical lead gloves. Finally, we discussed the radiation risks associated to the exhibition of a single specimen. The results, compared to the safety standards of the EU Directive 13/59, show that the exhibition of uraniferous samples with activity of a few MBq do not need specific radioprotection requirements nor for the involved personnel nor for visitors.

How do sports injury epidemiological outcomes vary depending on athletes' response rates to a weekly online questionnaire? An analysis of 39-week follow-up from 391 athletics (track and field) athletes.

To explore how sports injury epidemiological outcomes (i.e., prevalence, average prevalence, incidence, burden, and time to first injury) vary depending on the response rates to a weekly online self-reported questionnaire for athletes. Weekly information on athletics injuries and exposure from 391 athletics (track and field) athletes was prospectively collected over 39 weeks (control group of the PREVATHLE randomized controlled trial) using an online self-reported questionnaire. The data were used to calculate sports injury epidemiological outcomes (i.e., prevalence, average prevalence, incidence, burden, and time to first injury) for sub-groups with different minimum individual athletes' response rates (i.e., from at least 100%, at least 97%, at least 95%, … to at least 0% response rate). We then calculated the relative variation between each sub-group and the sub-group with a 100% response rate as a reference. A substantial variation was considered when the relative variation was greater than one SD or 95% CI of the respective epidemiological outcome calculated in the sub-group with a 100% response rate. Of 15 249 expected weekly questionnaires, 7209 were completed and returned, resulting in an overall response rate of 47.3%. The individual athletes' response rates ranged from 0% (n = 51) to 100% (n = 100). The prevalence, average weekly prevalence, and time to first injury only varied substantially for the sub-groups below a 5%, 10% and 18% minimum individual response rate, respectively. The incidence and injury burden showed substantial variations for all sub-groups with a response rate below 100%. Epidemiological outcomes varied depending on the minimum individual athletes' response rate, with injury prevalence, average weekly prevalence, and time to first injury varying less than injury incidence and injury burden. This highlights the need to take into account the individual response rate when calculating epidemiological outcomes, and determining the optimal study-specific cut-offs of the minimum individual response rate needed.

An Eco-friendly Mangifera indica Leaves Extract Corrosion Inhibitor for Stainless Steel in Acidic Medium

Corrosion of metals and alloys is one of the most frequent problems encountered in chemical and process industries. Inefficient corrosion control measures typically lead to an increased risk of unplanned downtime, huge economic loss, environmental damage, and health and safety hazards. Hence, it is essential to develop environment-friendly and cost-effective corrosion inhibitors over existing toxic anticorrosive agents. The main objective of this work is to examine the efficacy of eco-friendly ethanolic extract of Mangifera indica leaves (MIL) in different concentrations as a green corrosion inhibitor for stainless steel (SS-316L) under an acidic environment. The inhibition efficiency of Mangifera indica leaves extract in 1 M hydrochloric acid (HCl) was evaluated by conventional weight loss method along with adsorption isotherm analysis. Chemical compounds present in leaf extract and changes in surface morphology of SS-316L samples were assessed using Fourier Transform Infrared spectroscopy (FTIR) and Field Emission Scanning Electron Microscopy (FE-SEM) provided with elemental analysis. The results of the weight loss method revealed that the inhibition efficiency increases with increasing MIL extract concentration due to higher surface coverage. The highest inhibition efficiency of almost 63.43% in 14 days and minimum corrosion rate of 0.433 mm per year was obtained for SS-316 L in 1.0 M HCl with 1000 ppm concentration. The adsorption of MIL extract on SS-316L surface followed Freundlich adsorption isotherm, and the obtained value of free Energy of adsorption (ΔG˚ads = – 9.20 kJ.mol-1) indicates the physical adsorption mechanism. The developed regression-based models can predict the corrosion rate as a function of inhibitor concentration and exposure time with good accuracy (>80%). Thus, the present findings demonstrate that Mangifera indica L. leaves extract can suitably be applied as an inexpensive, non-toxic, biodegradable, efficient green corrosion inhibitor for the protection of stainless steel in acidic media.

Heart rate reduction during voluntary deep diving in free-ranging loggerhead sea turtles.

Air-breathing vertebrates exhibit cardiovascular responses to diving including heart rate reduction (diving bradycardia). Field studies on aquatic mammals and birds have shown that the intensity of bradycardia can vary depending on diving behaviour, such as the depth of dives and dive duration. However, in aquatic reptiles, the variation in heart rate during deep dives under natural conditions has not been fully investigated. In this study, we released five loggerhead sea turtles (Caretta caretta) outfitted with recorders into the sea and recorded their electrocardiogram, depth, water temperature and longitudinal acceleration. After 3days, the recorders automatically detached from the turtles. The heart rate signals were detected from the electrodes placed on the surface of the plastron. The mean (±s.d.) heart rate of 12.8±4.1beatsmin-1 during dives was significantly lower than that of 20.9±4.1beatsmin-1 during surface periods. Heart rate during dives varied with dive depth, although it remained lower than that at the surface. When the turtle dived deeper than 140m, despite the relatively high flipper stroke rate (approximately 19strokesmin-1), the heart rate dropped rapidly to approximately 2beatsmin-1 temporarily. The minimum instantaneous heart rate during dives was lower at deeper dive depths. Our results indicate that loggerhead sea turtles show variations in the intensity of diving bradycardia depending on their diving behaviour, similar to that shown by marine mammals and birds.

Molecular identification of Crimean-Congo haemorrhagic fever virus in Hyalomma rufipes and Amblyomma variegatum in the Upper East Region of Ghana.

Sampled ticks were screened for Crimean-Congo haemorrhagic fever virus (CCHFV) using an assay that targets the nucleoprotein gene region of the S segment, a conserved region of the CCHFV genome. Minimum infection rates of 0.34% and 0.10% were obtained when testing pools of Hyalomma rufipes and Amblyomma variegatum, respectively. Next-generation sequencing and phylogenetic analysis showed that the S and L segments of the CCHFV isolate clustered with those of similar isolates of genotype III. However, analysis of the M segment showed that reassortment had occurred, causing this segment to cluster with those of isolates of genotype I, providing the first evidence of such an occurrence in Ghana.

Long-term polyethylene wear rates and clinical outcomes of oxidized zirconium femoral heads on highly cross-linked polyethylene in total hip arthroplasty.

Oxidized zirconium (OxZi) and highly cross-linked polyethylene (HXLPE) were developed to minimize wear and risk of osteolysis in total hip arthroplasty (THA). However, retrieval studies have shown that scratched femoral heads may lead to runaway wear, and few reports of long-term results have been published. The purpose of this investigation is to report minimum ten-year wear rates and clinical outcomes of THA with OxZi femoral heads on HXLPE, and to compare them with a retrospective control group of cobalt chrome (CoCr) or ceramic heads on HXLPE. From 2003 to 2006, 108 THAs were performed on 96 patients using an OxZi head with a HXLPE liner with minimum ten-year follow-up. Harris Hip Scores (HHS) were collected preoperatively and at the most recent follow-up (mean 13.3 years). Linear and volumetric liner wear was measured on radiographs of 85 hips with a minimum ten-year follow-up (mean 14.5 years). This was compared to a retrospective control group of 45 THAs using ceramic or CoCr heads from October 1999 to February 2005, with a minimum of ten years' follow-up. Average HHS improved from 50.8 to 91.9 and 51.0 to 89.8 in the OxZi group and control group, respectively (p = 0.644), with no osteolysis in either group. Linear and volumetric wear rates in the OxZi group averaged 0.03 mm/year and 3.46 mm3/year, respectively. There was no statistically significant difference in HHS scores, nor in linear or volumetric wear rate between the groups, and no revision for any indication. The radiological and clinical outcomes, and survivorship of THA with OxZi femoral heads and HXLPE liners, were excellent, and comparable to CoCr or ceramic heads at minimum ten-year follow-up. Wear rates are below what would be expected for development of osteolysis. OxZi-HXLPE is a durable bearing couple with excellent long-term outcomes.

A two-dimensional perspective of the rotational evolution of rapidly rotating intermediate-mass stars

Context. Recently, the first successful attempt at computing stellar structure and evolution models in two dimensions was presented with models that include centrifugal deformation and self-consistently compute the velocity field. Aims. The aim of the present study is to explore the rotational evolution of two-dimensional models of stars rotating at a significant fraction of their critical angular velocity. From the predictions of these models, we aim to improve our understanding of the formation of single Be stars. Methods. Using the ESTER code, which solves the stellar structure of a rotating star in two dimensions with time evolution, we computed evolution tracks of stars of between 4 and 10 M⊙ for initial rotation rates ranging between 60 and 90% of the critical rotation rate. Furthermore, we compute models for both a Galactic metallicity and an SMC metallicity. Results. A minimum initial rotation rate at the start of the main sequence is needed to spin up the star to critical rotation within its main sequence lifetime. This threshold depends on the stellar mass, and increases with increasing mass. The models do not predict any stars above 8 M⊙ to reach (near-)critical rotation during the main sequence. Furthermore, we find the minimum threshold of initial angular velocity is lower for SMC metallicity than for Galactic metallicity, which is in agreement with the increased fraction of observed Be stars in lower metallicity environments. The strong difference in the rotational evolution between different masses is not predicted by any one-dimensional stellar evolution models. Conclusions. Our self-consistent two-dimensional stellar evolution models provide further insight into the rotational evolution of intermediate-mass stars, and our predictions are consistent with observations of velocity distributions and the fraction of Be stars amongst B-type stars. We find that stars with a mass above 8 M⊙ do not increase their fraction of critical rotation during the main sequence. As a fraction of stars above 8 M⊙ have been observed to display the Be phenomenon, other processes or formation channels must be at play, or, alternatively, critical rotation is not required for the Be phenomenon above this mass.

The Role of Temperature, Wind Speed, and Precipitation on the Abundance of Culex Species and West Nile Virus Infection Rate in Rural West-Central Illinois.

While most research on West Nile virus (WNV) and its main vector, the Culex mosquito, has been conducted in laboratory or urban settings, studies with field-caught mosquitoes in rural areas, such as west-central Illinois, are lacking. The objective of this research was to investigate key abiotic factors using macroclimate data, including temperature, precipitation, and wind speed, to determine their influence on field-caught mosquito abundance in 4 rural counties in Illinois from 2014 to 2016. Additionally, the relationship between minimum infection rate (MIR) and thermal time was examined. Using gravid traps at 15 sites, Culex mosquitoes were collected twice a week. A total of 5,255 adult female Culex mosquitoes (Cx. pipiens, Cx. quinquefasciatus, and Cx. restuans) were collected in 2014; 9,138 in 2015; and 5,702 in 2016. Regression models were developed based on outcomes of relationships between field-caught mosquitoes and abiotic factors. Precipitation and thermal time had the most significant relationship with mosquito abundance (r2 = 0.993 and r2 = 0.993, respectively), while wind speed was less (r2 = 0.714). The greatest number of Culex and the highest annual MIR were observed in 2015, which was also the driest of the 3 sampling seasons. Mosquito abundance was observed to increase with warmer degree days and MIR was found to increase with abundance in mosquitoes. These models can be used for other mosquito surveillance and monitoring studies in various climate types and environments.

QoE-Aware Network Pricing, Power Allocation, and Admission Control

In wireless communications, focusing on end-user satisfaction and maximizing network operators' revenue are emerging business challenges. In this paper, we investigate the price-based power allocation problem where, first, base stations (BSs) set prices by maximizing users' utility modeled by their mean opinion score (MOS). Then, each user's optimal power is set by maximizing operator revenue while ensuring the minimum data rate for each user. We propose a hybrid MOS-based pricing method to model users' utility instead of the conventional achievable rate approach. Our hybrid approach applies a machine learning algorithm to model the MOS of the call service in terms of the received signal strength indicator (RSSI). In terms of MOS and outage probability, our proposed method outperforms the rate-based pricing method and the conventional objective MOS models. In addition, we consider a joint admission control and price-based power allocation problem. When a new user requests to connect, a central controller determines whether or not to accept the new connection based on the system's MOS and average outage probability. The results demonstrate a trade-off between the number of users admitted and their level of satisfaction, providing operators with crucial knowledge about how to use their network resources more effectively.

Optimization of multi-staged Tesla valve using response surface methodology

The multi-stage Tesla valve (MSTV), which consists of multiple identical TVs in series, enhances the effectiveness of the TV. To further improve the performance of the MSTV, an improved MSTV has been proposed by designing each arch channel in the typical MSTV as two separate arch channels: the inner arch channel and the outer arch channel. Response surface methodology is used to optimize the improved MSTV, with the maximum mass flow rate in forward flow and the minimum mass flow rate in reverse flow as two optimization objectives. The non-dominated sorting genetic algorithm is employed to obtain the Pareto solution set, resulting in the optimized design for the improved MSTV (named short-baffle improved MSTV). Theoretical simulations and experimental research are conducted on a typical MSTV, an improved MSTV, and a short-baffle improved MSTV, and their flow resistance ratios (FRRs) are obtained. The FRR of the short-baffle improved MSTV has improved by an average of 8.70% compared to that of typical MSTV. At low inlet pressures, the increase in FRR is approximately 1.4% higher than that at high inlet pressures. The research results indicate that the FRR of the shot-baffle improved MSTV is greater than that of a typical MSTV, and to some extent, the performance of an MSTV is enhanced under low inlet pressure.

Optimization of magnetic coupling mechanism of dynamic wireless power transfer based on NSGA-II algorithm

Optimization of magnetic coupling mechanism is an important way to improve the performance of a dynamic wireless power transfer system. Inspired by the common radial magnetic core for circular coils, a new radial magnetic core for rectangular coils is adopt. Through simulation and experimental results comparison, which has higher coupling coefficient with the same core area. Combined with the magnetic circuit analysis, the magnetic flux leakage and conduction regions are divided into magnetic fluxes with different shapes, which magnetic resistances are calculated respectively. Based on the simulation results, parameter distributions of fluxes under different conditions are obtained. Therefore, the expressions of the coupling coefficient k of the adopt magnetic cores and coils and the design parameters of coils and cores are obtained. Taking the maximum k and the minimum rate of change of coupling coefficient with 100 mm displacement as the optimization objectives, a multi-objective optimization solution is carried out by using NSGA-II algorithm. The coil optimization scheme is obtained and verified by experiments. k and Δk are 0.442 and 6.8% respectively, and the errors are less than 5%. In the optimization process, there is no simulation model constructed. The optimization modeling combined of magnetic field segmentation method and parameter fitting has lower complexity and calculation time of optimization.