Efficiency Curves Research Articles

Simulating the Sensitivity to Stellar Point Sources of Chandra X-Ray Observations

The Chandra Cygnus OB2 Legacy Survey is a wide and deep X-ray survey of the nearby and massive Cygnus OB2 association. The survey has detected ∼8000 X-ray sources, the majority of which are pre-main-sequence X-ray-emitting young stars in the association itself. To facilitate quantitative scientific studies of these sources, as well as the underlying OB association, it is important to understand the sensitivity of the observations and the level of completeness the observations have obtained. Here we describe the use of a hierarchical Monte Carlo simulation to achieve this goal by combining the empirical properties of the observations, analytic estimates of the source verification process, and an extensive set of source detection simulations. We find that our survey reaches a 90% completeness level for a pre-main-sequence population at the distance of Cyg OB2 at an X-ray luminosity of 4 × 1030 erg s−1 and a stellar mass of 1.3 M ⊙ for a randomly distributed population. For a spatially clustered population such as Cyg OB2 the 90% completeness level is reached at 1.1 M ⊙ instead, as the sources are more concentrated in areas of our survey with a high exposure. These simulations can easily be adapted for use with other X-ray observations and surveys, and we provide X-ray detection efficiency curves for a very wide array of source and background properties to allow these simulations to be easily exploited by other users.

Transformative Learning, Priming, and Simulation Timing: A Randomized Controlled Pilot Study Among Emergency Medicine Residents.

Background Traditionally, learning is thought to occur best when prerequisite cognitive background information is delivered before simulation training. More recent studies have attempted to analyze the transformative nature of simulation by placing simulation before didactics. However, these studies were flawed as they provided background on the subject before the simulation itself. Our study aims to isolate the transformative effect of simulation and answer the question of whether lecture or simulation should come first. Methodology We designed a novel simulation session and accompanying lecture for 18 Emergency Medicine residents in all three years of training regarding a subject they were entirely unfamiliar with, the emergent management of a left ventricular assist device (LVAD). The residents were randomized into two groups. One group had the lecture (8/18) before their simulation, while the other group (10/18) had the simulation first and the lecture afterward, testing the motivational nature. Thereafter, both groups responded to a post-session survey with Likert-style and open-ended comment questions to assess the reaction to the session and a knowledge-based multiple-choice question test. Results Both groups did not score significantly differently on either the immediate post-test or a retention post-test that we administered four weeks later. Three of eight participants reported in open comments that they were much more comfortable with a lecture-first than a simulation-first format. Conclusions Despite controlling for some of the limitations of previous studies, our results including learners' preferences do not support a transformation in the sequence of clinical skills learning. Until other larger studies prove the opposite, we recommend continuing with the lecture followed by the simulation sequence as per existing conceptual simulation learning frameworks.

Energy analysis and control scheme optimizations for a recuperated gas turbine with variable power offtakes/inputs

An innovative hybrid electric propulsion system (HEPS) is used for recuperated gas turbine (RGT) to avoid partial-load efficiency deterioration. Power offtakes/inputs of high and low-pressure shafts can be regulated by electric machines to achieve decoupling control in the innovative HEPS. The HEPS brings higher heating temperature in the combustor and significantly higher thermal efficiency at partial-load by optimizing the control scheme. A component-level model is used to conduct energy and performance analyses for RGT. The control scheme is optimized to enhance partial-load efficiency and protect RGT from temperature overrun, rotational speed overrun, and compressor surge.The optimal control scheme keeps the combustor exit temperature constant at the maximum restricted value to attain minimum combustor exergy loss under partial-load. The optimal control scheme brings smaller surge margins, but it successfully reverses the deterioration trend of efficiency with decreased load. The thermal efficiency of the original RGT decreases by 8.2 % as the load decreases from 100 to 40 %. The HEPS makes the efficiency curve of the RGT almost keep horizontal as the load ranges from 100 to 40 %. The specific fuel consumption decreases by 29.1 %, and the thermal efficiency increases by 11.5 % at 40 % load, compared to the original RGT.

Optimization Analysis on the Transmission Characteristics of Multipurpose Power Transmission Devices

Particularly crucial throughout the mode transition procedure is the transmission properties of hydro–mechanical composite transmission devices. This paper describes a multipurpose power transmission device that integrates hydrostatic, hydro-mechanical, and mechanical transmission and mainly discusses the transmission characteristic optimization problem from the perspective of speed regulation characteristics, shift strategy, and efficiency characteristics. The kinematic and dynamic analysis of the transmission system, the assembly scheme, and relevant parameters of the power transmission device are analyzed, and the speed regulation characteristic curve is obtained. The shift strategy of power transmission devices involving clutches and brakes during the whole speed regulation process and the best switch time of each component are found. The efficiency expression of the static pressure system is obtained from the efficiency model of the pump-control-motor system, and the efficiency of the multi-purpose power transmission device is obtained using the efficiency definition method. The fitting curves of hydrostatic system efficiency are determined using experimental data, and the efficiency of the hydro–mechanical composite power transmission system is obtained using the conversion mechanism method. The results show that the shift quality of power transmission devices can be improved greatly by controlling the switch sequence of clutches and brakes reasonably.

Dynamic Evolution and Convergence Analysis of the Ecological Efficiency of China’s Fisheries

The dynamic evolution and regional heterogeneity of fishery efficiency development must be explored from an ecological perspective to reveal the spatial pattern of fishery ecological efficiency. Thus, taking 30 provinces/cities in China between 2006 and 2020 as research objects, we measured the level of the fishery ecological efficiency and regional fishery ecological efficiency convergence indexes using the superefficiency and convergence indexes, respectively. We found the following: (1) The ecological efficiency of China’s fishery shows a wavelike upward trend with significant fluctuations, but the overall efficiency level is not high. (2) The development of regional fishery ecological efficiency is not well coordinated; however, the variation curve of fishery ecological efficiency in the eastern and central regions is gradually decreasing. (3) A trend of “catching up and surpassing” is observed in the development of fishery ecological efficiency in various regions of China, and regional fishery ecological efficiency gradually converges to the regions’ respective steady-state levels over time. The results indicate a significant gap in regional fishery ecological efficiency, as well as polarization; areas with lower fishery efficiency are catching up with high-efficiency areas at different speeds, and regional fishery ecological efficiency is stabilizing.

The effect of two-part dead layer thickness on the efficiency curve of a P-TYPE HPGe detector calculated using the Monte Carlo method

The full energy peak efficiency (FEPE) of a gamma ray obtained from experimental studies using a high purity germanium detector (HPGe) can be easily reproduced by simulating the experiment in any desired geometry and energy range with Monte Carlo (MC) simulation methods. However, the dead layer (DL) thickness, which is one of the geometric information provided by the manufacturer, changes over time and affects the efficiency calculation, so it must be determined and compared with the initial value for the increases during the life-time of the detector. In this study, the general-purpose MC code PHITS and the special-purpose MC code GESPECOR were used to simulate a p-type HPGe detector and to determine the thickness of the frontal and lateral dead layer. As a result, it was observed that the frontal dead layer thickness increased from 0.7 mm to 1.075 mm, and the lateral dead layer thickness increased from 0.7 mm to 1.7 mm after 7 years of operation of the detector. This increase in dead layer thickness causes both a decrease in the detector's active volume and a decrease in efficiency in the problematic low-energy region.

Effect of variable speed conditions on the internal flow characteristics of a multiphase pump

The multiphase pump is an important device in the mixing and transmission technology for oil and gas. It simplifies the entire process of oil and gas extraction and transmission. In actual engineering, the gas volume fraction (GVF) of the fluid being transported is constantly changing, and this change has an important impact on the internal flow characteristics of the pump. The multiphase pump also needs to change the operating speed to adapt to this change to keep its internal flow field and external characteristics in a good operating range. In this work, the internal flow characteristics of the pump unit under different velocity conditions for the bullet flow type are compared and analyzed. It can be concluded that the higher the rotational speed, the better the pressure increment performance. The lower efficiency of the multiphase pump under high-speed conditions is mainly caused by the increase in the velocity difference between gas and liquid phases in the back area of the guide vane outlet, which leads to an increase in a vortex. Unlike the design point condition, the efficiency curves of the two high-speed conditions show an increasing trend in the design flow interval from 0.1 times to 1.2 times. It shows that an increase in speed causes the high-efficiency zone of the multiphase pump to shift to the high-flow rate zone. Finally, an experimental investigation of the variable velocity condition was performed to verify the validity of the numerical simulation.

Optimal design of impeller for self-priming pump based on orthogonal method

In order to improve the efficiency of the self-priming pump in the outdoor emergency rescue mobile pump truck, this paper took the key energy conversion component-impeller as the target and used the orthogonal experimental design method to optimize its hydraulic performance. Firstly the numerical calculations were compared with the experimental results to confirm the reliability of the calculation method. Then, L9 (34) orthogonal design was applied to investigate the influence of the impeller diameter, the blade outlet width, the blade wrap angle and the number of blades on the hydraulic performance of the self-priming pump. Through range analysis, the order of influence of each influencing factor on the head and efficiency of the self-priming pump was determined, and finally obtained the optimal parameter combination scheme. The results show that the optimized self-priming pump exceeds the head of the prototype pump at all flow conditions, and the efficiency curve at high flow conditions is significantly improved and has a wide high efficiency zone.

Transient numerical investigation on hydraulic performance and flow field of multi-stage centrifugal pump with floating impellers under sealing gasket damage condition

Multi-stage centrifugal pumps with floating impellers provide a convenient means of adjustment to meet diverse head requirements. These pumps utilize sealing gaskets to minimize leakage losses and restrict impeller axial motion. However, the impact of sealing gasket breakage on hydraulic performance and internal flow remains uncertain. To investigate this, a novel dynamic mesh simulation method is proposed to enable simultaneous axial motion and rotation of the impeller. Validation of numerical simulations with experiments is performed. Transient hydraulic performance is influenced by impeller axial motion, with a lagging flow field response. Head coefficient and efficiency curves exhibit asymmetric triangular functions with higher fluctuations compared to impeller with fixed axial position. At the design condition, with the impeller floating, the head coefficient ranges from 0.7 to 1.9, while the efficiency ranges from 29.7% to 60.1%. Among the various loss ratios, the hydraulic loss ratio exhibits the highest magnitude, followed by the leakage loss ratio, with the shroud friction loss ratio being the smallest. Entropy production reveals the significant influence of impeller oscillation on local flow loss. The axial motion of the impeller causes drastic velocity and pressure fluctuations in both time and space.

Serum Activities of Paraoxonase 1 (PON1) in Predicting Liver Damage Among Patients Diagnosed With Hepatocellular Carcinoma: A Case-Control Study.

Introduction Hepatocellular carcinoma (HCC)is one of the most common cancers in the world and unless diagnosed timely has limited options for treatment. Paraoxonase(PON) isa glycosylated proteinthat has been implicated in antioxidant and other biochemical functions.Paraoxonase 1 (PON1)is an esterase associated with high-density lipoprotein (HDL) particles. The present study was carried out to assess the PON1 activity and compare it with the standard liver function tests (LFTs) in assessing the predictability of liver damage among patients diagnosed with HCC. Methods This case-control study was carried out in the Department of Biochemistry attached to Great Eastern Medical School and Hospital, Srikakulam, Andhra Pradesh. Serum PON1 activities and LFTs like total bilirubin, direct bilirubin, alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), total protein, and albumin were estimated in 30 patients diagnosed with HCC and 30 healthy persons. All the parameters were estimated using standard biochemical methods.The data was analyzed using GraphPad Prism version 6.0 (GraphPad Software, Inc).A probability (p) value <0.05 was considered to be statistically significant. Receiver operating characteristic curve (ROC) analysis was performed to assess the area under the curve (AUC) for accuracy, sensitivity, specificity, and diagnostic efficiency. Results The serum activities of PON1 had identical sensitivity (70%) to albumin (70%) and were superior to other tested parameters. Additionally, PON1 activities showed lower specificity (86.67%) than the other tested parameters. ROC analysis showed increased diagnostic efficacy (DE) of PON1 (DE=78.3%; p<0.0001) when compared with total bilirubin (DE=76.6%; p=0.0039), direct bilirubin (DE=74.9%; p=0.04), ALT (DE=73.30%; p=0.0006), and total protein (DE=71.6%; p=0.0005). However, the DE of PON1 was comparable with AST (DE=81.60%; p<0.0001), ALP (DE=79.9%; p<0.0001), and albumin (DE=83.30%, p<0.0001). Conclusions Serum activities of PON1 could be used as a diagnostic marker for assessing liver damage among HCC patients.

Correlations between iodine uptake, invasive CT features and pleural invasion in adenocarcinomas with pleural contact

Pleural contact in lung cancers does not always imply pleural invasion (PI). This study was designed to determine whether specific invasive CT characteristics or iodine uptake can aid in the prediction of PI. The sample population comprised patients with resected solid lung adenocarcinomas between April 2019 and May 2022. All participants underwent a contrast enhanced spectral CT scan. Two proficient radiologists independently evaluated the CT features and iodine uptake. Logistic regression analyses were employed to identify predictors for PI, via CT features and iodine uptake. To validate the improved diagnostic efficiency, accuracy analysis and ROC curves were subsequently used. A two-tailed P value of less than 0.05 was considered statistically significant. We enrolled 97 consecutive patients (mean age, 61.8 years ± 10; 48 females) in our study. The binomial logistic regression model revealed that a contact length > 10 mm (OR 4.80, 95% CI 1.92, 11.99, p = 0.001), and spiculation sign (OR 2.71, 95% CI 1.08, 6.79, p = 0.033) were independent predictors of PI, while iodine uptake was not. Enhanced sensitivity (90%) and a greater area under the curve (0.73) were achieved by integrating the two aforementioned CT features in predicting PI. We concluded that the combination of contact length > 10 mm and spiculation sign can enhance the diagnostic performance of PI.

Dust-removal performance of an improved spherical cylindrical ECP under magnetic confinement effect

In order to further improve the trapping effect of fine particles, an improved electrostatic cyclone precipitator (ECP) was proposed. The electromagnetic dust-removal mechanism of spherical cylindrical ECP was revealed, and the influences of flue gas velocity on the dust-removal effect of fine particles with and without magnetic confinement effect were discussed. The results show that the overall efficiency curve of fine particles shows a ' hump ' type with the change of flue gas velocity, and the increase of magnetic induction intensity promotes the hump to move to the low flue gas velocity area. Increasing magnetic induction intensity can improve the trapping performance of spherical cylindrical magnetically constrained ECP, and the improvement effect weakens gradually when the same amplitude increases.

Light yield and thermal quenching of Ce3+ and Pr3+ co-doped LaBr3:Sm2+ near-infrared scintillators

LaBr3:Ce3+ is a compound with excellent scintillation properties, but its ultraviolet emission does not match well with the detection efficiency curves of silicon based photodetectors. In this work, Sm2+ is studied as an activator for LaBr3 as its near-infrared emission can be detected with close to 100% efficiency by such photodetectors. LaBr3:Sm2+ single crystals were grown with and without co-doping of Ce3+ or Pr3+. The samples were studied by means of X-ray excited and photoluminescence spectroscopy at temperatures between 10 K and 300 K. Their spectroscopic properties are compared to LaBr3:Ce3+ and LaBr3:Eu2+. The effect of using Ce3+ or Pr3+ as scintillation sensitiser for Sm2+ is assessed. It is found that energy transfer from host to Sm2+ greatly improves upon Ce3+ co-doping, but the quenching temperature of the Sm2+ emission decreases. The quenching mechanism of both the Ce3+ and Sm2+ emission in LaBr3 is elaborated on. Furthermore, the effect of charge compensating defects on the light yield and spectroscopic properties is discussed.

Multivariate Regression Models for Predicting Pump-as-Turbine Characteristics

Installing pumps as turbines (PaTs) in water distribution networks can recover otherwise wasted energy, as well as reduce leakage caused by high water pressure. However, a barrier to their implementation is the lack of information on their performance in turbine mode. Previous studies have proposed models to predict PaT characteristics based on pump best efficiency points (BEPs), using regressions with one or two dependent variables, or more complex artificial neural networks (ANNs). While ANNs were found to improve the accuracy of predictions, these models are known to be unstable with small datasets. Other types of regressions with multiple variables have not been explored. Furthermore, because only small datasets are available to train these models, multivariate regression methods could yield better results. The present study develops multivariate regression models to predict BEPs and characteristic curves of PaTs. A database of 145 BEPs and 196 characteristic curve PaT experimental records was compiled from previous literature. Twenty-four types of multi-variate regressions, as well as ANN were compared, with dimensioned and dimensionless versions of the datasets. The multivariate regression models consistently outperformed previous models, including ANN. The R2 of the head and efficiency curves were 0.997 and 0.909, respectively. Results also showed that XGB regressors and a dimensionless dataset yielded the best-fit models overall. The high accuracy of the models, combined with their lower computational cost compared to ANN, make them a robust solution for selecting PaTs in practice.

An interval water demand prediction method to reduce uncertainty: A case study of Sichuan Province, China

Effective prediction of water demand is a prerequisite for decision makers to achieve reliable management of water supply. Currently, the research on water demand prediction focuses on point prediction method. In this study, we constructed a GA-BP-KDE hybrid interval water demand prediction model by combining non-parametric estimation and point prediction. Multiple metaheuristic algorithms were used to optimize the Back-Propagation Neural Network (BP) and Kernel Extreme Learning Machine (KELM) network structures. The performance of the water demand point prediction models was compared by the Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), Kling-Gupta Efficiency (KGE), computation time, and fitness convergence curves. The kernel density estimation method (KDE) and the normal distribution method were used to fit the distribution of errors. The probability density function with the best fitting degree was selected based on the index G. The shortest confidence interval under 95% confidence was calculated according to the asymmetry of the error distribution. We predicted the impact indicator values for 2025 using the exponential smoothing method, and obtained water demand prediction intervals for various water use sectors. The results showed that the GA-BP model was the optimal model as it exhibited the highest computational efficiency, algorithmic stability, and prediction accuracy. The three prediction intervals estimated after adjusting the KDE bandwidth parameter covered most of the sample points in the test set. The prediction intervals of the four water use sectors were evaluated as F values of 1.6845, 1.3294, 1.6237, and 1.3600, which indicates high accuracy and quality of the prediction intervals. The mixed water demand interval prediction based on GA-BP-KDE reduces the uncertainty of the point prediction results and can provide a basis for water resource management by decision makers.

Evaluation of the environmental sustainability of SOFC-based cogeneration systems in commercial buildings

In order to achieve the European Union (EU)’s climate targets, efficient and sustainable solutions must be developed. In this context, the building sector has a key role to play in the transition to a decarbonized society. Cogeneration is considered an efficient solution that enables better use of fuel energy to supply buildings with heat and electricity. In particular, fuel cell-based cogeneration systems have shown promising performance, thus attracting considerable attention in recent years. The main goal of this study is to analyze the environmental impact of Solid Oxide Fuel Cell (SOFC) cogeneration systems, focusing on commercial buildings. The analysis was performed in the framework of the H2020 Comsos project, whose aim is to investigate the techno-economic and environmental feasibility of SOFC-based systems in non-residential buildings. An MILP-based optimization framework was developed to address the optimal design and operation of energy systems with the inclusion of SOFC-based cogeneration solutions. Electrical and thermal efficiency curves, derived from real SOFC operation, were used to improve the accuracy of the SOFC performance simulation. A sensitivity analysis on the carbon intensity of electricity was carried out to explore the role of the SOFC technology under different levels of electrical grid decarbonization. It was found that natural gas-fed SOFC systems become environmentally advantageous (in terms of CO2 emissions) when the carbon intensity of electricity is higher than ∼ 300 gCO2/kWh.

Study on the thermal oxidation of oleic, linoleic and linolenic acids by synchrotron radiation photoionization mass spectrometry.

Cooking oil fumes contain numerous hazardous and carcinogenic chemicals, posing potential threats to human health. However, the sources of these species remain ambiguous, impeding health risk assessment, pollution control and mechanism research. To address this issue, the thermal oxidation of three common unsaturated fatty acids (UFAs), namely oleic, linoleic and linolenic acids, present in vegetable oils was investigated. The volatile and semi-volatile products were comprehensively characterized by online synchrotron radiation photoionization mass spectrometry (SR-PIMS) with two modes, which were validated and complemented using offline gas chromatography (GC)/MS methods. Tunable SR-PIMS combined with photoionization efficiency curve simulation enabled the recognition of isomers/isobars in gaseous fumes. SR-PIMS revealed over 100 products, including aldehydes, alkenes, furans, aromatic hydrocarbons, etc., such as small molecules of formaldehyde, acetaldehyde, acrolein, ethylene and furan, which are not readily detected by conventional GC/MS; and some unreported fractions, e.g. ketene, 4-ethylcyclohexene and cycloundecene(E), were also observed. Furthermore, real-time monitoring of product emissions during the thermal oxidation of the three UFAs via SR-PIMS revealed that linolenic acid may be the major source of acrolein. SR-PIMS has been demonstrated as a powerful technique for online investigation of cooking oil fumes. This study achieved comprehensive characterization of volatile and semi-volatile products from the thermal oxidation of oleic, linoleic and linolenic acids, facilitating the traceability of species in cooking fumes and aiding in exploring the thermal reactions of different vegetable oils.

Ionization of aluminum clusters

Near-threshold photoionization cross sections for several aluminum clusters have been estimated from the ionization efficiency curves. Their magnitude raises the possibility that the edge of a collective electron resonance (surface plasmon) may contribute to the photoemission channel. On the other hand, electron impact ionization efficiently produces multiply charged metal cluster ions and is unaccompanied by noticeable fragmentation. Consequently it does not appear to involve collective excitations.

Research on Inertia Lifting of New Power System Based on VSG Double Sagging Optimization Control

With the development of new energy sources, the power grid inertia declines rapidly, which makes the frequency adjustment ability and the power system stability poor. The virtual synchronous generator (VSG) uses a control algorithm to simulate the synchronous generator, which improves the frequency stability of the grid, but the dynamic adjustment performance would likely be degraded. Moreover, the optimal values of the pivotal parameters such as virtual inertia and damping are difficult to determine. Therefore, a VSG optimization strategy of double sagging control and neural network prediction is proposed which can effectively enhance the voltage and frequency safety of the system. Simulating the characteristic equation of the generator, the small signal analysis model of VSG is built, and the initial value of J and D is completed. An artificial neural network is accomplished, and the weight is adjusted to change the J and D of VSG by analyzing and learning the power grid operation. The expected parameter value can be gained after many times of learning and the adaptive control of VSG is realized.

Moving Research-Based Learning in Life Sciences Upstream, and Beyond Borders: An International Group Research Project for High School Youth.

International cooperation beyond borders, institutions, and intergenerationally is an important aspect of science and research-based learning. Timing of learning also matters. Early exposure to group research-based learning can potentially have lasting positive impacts on youth and their careers in life sciences. Here, we report our work on the International Group Project (IGP), which builds on the International Biology Olympiad (IBO) organized in Yerevan, Armenia, in 2022. The IBO is an annual international competition for high school students held since 1990 around the world. We envisioned the IGP as a novel opportunity for life sciences research-based education among youth. We formed diverse IGP research teams 2 months before the IBO, and comprised high school students from 32 countries, communicating in a digital environment via videoconferencing. Each team formulated a research question in an IGP theme from five domains of life sciences: "Biomedicine," "Molecular and cell biology," "Bioinformatics and Artificial Intelligence," "Bionics and Biomimicry," "Across Species." Subsequently, team members collectively solved their research question by applying life sciences methodologies under supervision from a facilitator scientist. Each team created a poster based on their research and presented in-person to the public at a satellite activity at the IBO. A special subcommittee of the IBO International Jury graded posters and allocated prizes based on scientific ingenuity and presentation quality. This experience from the IGP lends evidence to the feasibility of research-based learning in life sciences for high school youth beyond borders. Moving research-based learning upstream and internationally is well poised to advance 21st century life sciences from both interdisciplinary and intergenerational standpoints. The historic impact of the COVID-19 pandemic suggests that youth engagement in research-based learning and innovation in life sciences is timely.