Performance Index Research Articles

Accurate object localization facilitates automatic esophagus segmentation in deep learning

BackgroundCurrently, automatic esophagus segmentation remains a challenging task due to its small size, low contrast, and large shape variation. We aimed to improve the performance of esophagus segmentation in deep learning by applying a strategy that involves locating the object first and then performing the segmentation task.MethodsA total of 100 cases with thoracic computed tomography scans from two publicly available datasets were used in this study. A modified CenterNet, an object location network, was employed to locate the center of the esophagus for each slice. Subsequently, the 3D U-net and 2D U-net_coarse models were trained to segment the esophagus based on the predicted object center. A 2D U-net_fine model was trained based on the updated object center according to the 3D U-net model. The dice similarity coefficient and the 95% Hausdorff distance were used as quantitative evaluation indexes for the delineation performance. The characteristics of the automatically delineated esophageal contours by the 2D U-net and 3D U-net models were summarized. Additionally, the impact of the accuracy of object localization on the delineation performance was analyzed. Finally, the delineation performance in different segments of the esophagus was also summarized.ResultsThe mean dice coefficient of the 3D U-net, 2D U-net_coarse, and 2D U-net_fine models were 0.77, 0.81, and 0.82, respectively. The 95% Hausdorff distance for the above models was 6.55, 3.57, and 3.76, respectively. Compared with the 2D U-net, the 3D U-net has a lower incidence of delineating wrong objects and a higher incidence of missing objects. After using the fine object center, the average dice coefficient was improved by 5.5% in the cases with a dice coefficient less than 0.75, while that value was only 0.3% in the cases with a dice coefficient greater than 0.75. The dice coefficients were lower for the esophagus between the orifice of the inferior and the pulmonary bifurcation compared with the other regions.ConclusionThe 3D U-net model tended to delineate fewer incorrect objects but also miss more objects. Two-stage strategy with accurate object location could enhance the robustness of the segmentation model and significantly improve the esophageal delineation performance, especially for cases with poor delineation results.

Evaluation of novel indices of walking performance taking oxygen desaturation into account during six-minute walk test in cardiovascular disease patients.

In pulmonary disease patients since oxygen desaturation during 6-min walk test (6MWT) affects walk distance (6MWD), some novel indices such as desaturation/distance ratio [DDR, oxygen desaturation area (DAO2)/6MWD] and distance-saturation product [DSP, 6MWD × minimum peripheral oxygen saturation (SpO2)] are evaluated. However, there has been no study examining these indices that consider exercise-induced desaturation (EID) in patients with cardiovascular disease. In 94 cardiovascular disease patients without pulmonary complications, 6MWT and echocardiography were performed at the entry of cardiac rehabilitation. SpO2 was measured during 6MWT using a continuously monitorable pulse oximeter, and DSP and DDR were calculated using minimum SpO2 and DAO2 [sum of (100-SpO2) per second during 6MWT], respectively. EID was defined as SpO2 decrease of ≥ 4% or minimum SpO2 of < 90% during 6MWT. DSP was slightly lower and DDR was markedly higher in patients with EID than in those without. When examining correlations of DSP and DDR with their components, DSP was correlated with 6MWD much closely than minimum SpO2, while DDR was correlated as closely with DAO2 as 6MWD. Furthermore, DAO2, but not minimum SpO2, had a direct correlation with 6MWD. As for associations with cardiac function, DSP was correlated with several cardiac parameters, but DDR was not correlated with any of these parameters. Our findings suggest that oxygen desaturation during 6MWT affects walking distance in cardiovascular disease patients even without pulmonary complications and that DDR is more appropriate than DSP as an index of walking performance that takes EID into consideration, independently of cardiac function.

Downscaling Future Precipitation over Mi Oya River Basin using Artificial Neural Networks

Studying future precipitation behaviour in river basins is essential for proper water resources and land-use planning within them, as this will help to reduce the risk and mitigate disasters that can occur in the future. General Circulation Models (GCMs) are used to study future precipitation fluctuations, which simulate large-scale climate variations under the effect of greenhouse gas changes. The GCM runs at a coarse spatial resolution which cannot be directly used for climate impact studies. Therefore, downscaling is required to extract the sub-grid and local scale information. This study examines the use of the Long Short-Term Memory (LSTM) neural network for climate downscaling to the Mi-Oya river basin in Sri Lanka using CNRM-CM5 and HadCM3 GCMs and observed annual data for 35 years. The precipitation data were extracted to cover Sri Lanka. Current downscaling models mostly use Convolutional Neural Networks (CNNs) to downscale GCMs. Out of 42 GCMs, two appropriate GCMs were chosen using the data analysis tool Data Integration and Analysis System (DIAS). The best predictor variables were chosen using the LASSO regression method. In this research, Machine Learning models were implemented using the Google TensorFlow platform. The Nash–Sutcliffe coefficient, Pearson correlation coefficient, and root-mean-square error performance indices were used to evaluate the performances of different downscaling models. Statistical downscaling was performed on the data at RCP 2.6, 4.5, and 8.5 using a LSTM. Subsequently, the changes that would take place by the year 2100 were analysed. The results show that precipitation will be reduced in the 2nd and 3rd decades of the 21st century, and precipitation will increase toward the 22nd century.

System reliability modeling and analysis for a marine power equipment operating in a discrete‐time dynamic environment

AbstractExploring on reliability modeling and analysis on a marine equipment in a dynamic environment is a meaningful and challenging issue, because the system commonly carries out the task at sea away from land and suffers a distinct influence of environment. Thus, a reliability model of a multi‐state repairable system operating in dynamic environment is developed by introducing the background of the marine power system in this paper. The novelty of the research lies in the modeling and computing methods are relatively innovative by employing the aggregated stochastic processes, Hadamard production and matrix‐analytic method. First, the working modes of the marine power system under several different kinds of conditions are introduced. Then, the evolution of both the system states and environment are described as discrete‐time Markov chains with multiple and different transition probability matrices. The failure probability and repair probability of components are also distinct in different environments. Furthermore, some performance indexes, especially the index relevant to the environment, are derived, respectively. Finally, the conclusion is obtained by a numerical example of the marine power system, which also illustrates the validity and applicability of the proposed model.

Neural mechanisms of the relationship between aerobic fitness and working memory in older adults: An fNIRS study

Abstract A growing number of studies have revealed that higher aerobic fitness is associated with better working memory (WM) performance in older adults. However, the underlying functional neural mechanisms of this association remain under debate. It has been reported that aging increases recruitment of the prefrontal cortex (PFC) during cognitive tasks, and that this is associated with task performance in a compensatory manner. Therefore, this study aimed to clarify the prefrontal activation pattern that is associated with the relationship between aerobic fitness and WM performance in older adults, focusing on age-related extended prefrontal recruitment. Forty-seven older adults (65–74 years, 29 females) and 49 younger adults (18–24 years, 23 female) performed verbal and spatial n-back tasks, which included 0-, 1-, and 2-back conditions. Reaction time (RT) and accuracy (ACC) were assessed as indices of task performance. Prefrontal activation during the experimental tasks was monitored using functional near-infrared spectroscopy (fNIRS) and analyzed using an adaptive GLM method. We compared task performance and prefrontal activation between age groups to find age-related prefrontal activation patterns. Only older adults underwent a graded exercise test (GXT) to determine their ventilation thresholds (VT) as a measure of aerobic fitness, and, subsequently, the relationships among aerobic fitness, n-back task performance, and prefrontal activation in older adults were examined using correlation analysis and mediation analysis controlling for possible covariates. A comparison of task performance between groups revealed that older adults had slower RT and lower ACC than did younger adults, especially in the higher WM load 2-back condition. Group comparisons of prefrontal activation showed that older adults exhibited additional or greater activation than younger adults mainly in the ventrolateral PFC (VLPFC) and front polar area (FPA) in both the verbal and spatial 2-back conditions. Correlation analysis showed a relationship between higher VT, shorter RT for the verbal 2-back condition, and greater prefrontal activation of the bilateral FPA and right VLPFC during verbal 2-back conditions in older adults. In addition, mediation analyses indicated the possibility of a mediation effect of the prefrontal activation on the relationship between VT and RT for the verbal 2-back condition. These results suggest that older adults with higher aerobic fitness levels recruited more extended PFC regions, possibly for compensatory activation, to enhance their performance of the verbal n-back task. This study sheds light on the neural mechanisms underpinning the relationship between aerobic fitness and cognitive function in older adults.

Radial ablation uniformity of cathode and design of double anode micro-cathode arc thruster

Micro-cathode arc thruster offers promising applications in micro–nanosatellite space missions owing to its simple structure, high specific impulse, and low power consumption. However, the non-uniform ablation of the cathode poses a significant limitation on the total impulse of micro-cathode arc thruster. This non-uniformity can be categorized into circumferential and radial types, with previous research primarily focusing on the influence of circumferential ablation non-uniformity. Nevertheless, it has been observed that radial ablation non-uniformity also affects the stability of the thruster, despite the lack of studies in this area. To investigate the mechanism behind the cathode radial ablation, a slice model has been designed to study the motion process of the cathode spots during a single discharge using a high-speed camera. From this analysis aims to identify the root cause of uneven cathode radial ablation. Building upon these findings, a double anode micro-cathode arc thruster has been devised to enhance the uniformity of cathode ablation. Experimental verification has been conducted to assess the performance of the double anode micro-cathode arc thruster. The results indicate that in the traditional micro-cathode arc thruster discharge process, the cathode spots do not migrate towards the outer layer covered by the shell. Instead, they extend to the surface of the shell along the contact area between the shell and cathode. This leads to unequal ablation between the inner and outer layers of the cathode. The double anode micro-cathode arc thruster effectively addresses these issues by providing two discharge channels that maintain the dynamic balance of electrode resistance and increase the ablation amount on the outer layer of the cathode. Consequently, the total impulse of the thruster improved significantly while ensuring the desired performance index.

Robust Fixed-Time Fault-Tolerant Control for USV with Prescribed Tracking Performance

The unmanned surface vessel (USV) is an emerging marine tool with its advantages of automation and intelligence in recent years; the good trajectory tracking performance is an important capability. This paper proposes a novel prescribed performance fixed-time fault-tolerant control scheme for an USV with model parameter uncertainties, unknown external disturbances, and actuator faults, based on an improved fixed-time disturbances observer. Firstly, the proposed observer can not only accurately and quickly estimate and compensate the lumped nonlinearity, including actuator faults, but also reduce the chattering phenomenon by introducing the hyperbolic tangent function. Then, under the framework of prescribed performance control, a prescribed performance fault-tolerant controller is designed based on a nonsingular fixed-time sliding mode surface, which guarantees the transient and steady-state performance of an USV under actuator faults and meets the prescribed tracking performance requirements. In addition, it is proved that the closed-loop control system has fixed-time stability according to Lyapunov’s theory. Finally, upon conducting numerical simulations and comparing the proposed control scheme with the SMC and the finite-time NFTSMC scheme, it is evident that the absolute error tracking performance index of the proposed control scheme is significantly lower, thus indicating its superior accuracy.

Performance analysis of different control models for smart demand–supply energy management system

Several features of innovative grid technologies can be deployed to improve the overall performance of the power system environment. This can be seen from the generation to the consumption of energy. The two-way communication of smart metering introduces the novel functionalities of the energy management system. This paper presents a practical implementation of using the intelligent metering system. It consists of implementing a nanogrid that optimally coordinates the energy from the solar panel, battery storage and utility grid to supply the end user. The developed model is validated with an optimal value of the state of charge of the distributed energy storage to maximise energy from the solar panel and battery storage while minimising the power received from the utility grid. A demand response scheme is employed to formulate the performance index of the energy management system using three optimal control models: adaptive open-loop control, adaptive closed-loop control and model predictive control schemes. The formulation of the performance index of each approach is a function of the energy flow from different resources depending on the power consumption. The three models have given different insights into the performance of the smart nanogrid, which may be used to the advantage of the grid owner or end user. Through the performance of the optimal strategies, it can be observed that energy management is ensured, and real-time monitoring of the entire system is guaranteed. The performance models facilitate the minimisation of the power from the utility, resulting in savings between 23.7% and 39.240% of the total energy demand from the end user. Besides, the system design is validated by an electrical system to form a real-world innovative nanogrid application in residential environments.

Assessment of performance and sustainability of waste heat dryer coupled with air conditioner unit during drying of banana slices

The present work presents the effective application of waste heat rejected from window air conditioning (AC) in a waste heat dryer (WHD) for drying plantain banana slices. The comparison between drying with the waste heat dryer coupled with an AC unit (ACWHD) and a natural convective indirect solar dryer (SD) reveals significant differences in drying kinetics, supply air conditions, and thermodynamic performance. The drying kinetics of banana slices obtained with ACWHD and SD were validated by revisiting the concepts of dryer performance index (DPI) and generalized drying curve. The temperature of the hot air supplied to the drying chamber in ACWHD was 48 °C while the relative humidity of the supply air was below 30 %. The thermodynamic performance assessment revealed that the exergetic efficiency was about 45 % and 16 % for ACWHD and SD respectively. The results of exergy based sustainable index and environment impact factor indicated the potential application of the waste heat of residual air from AC units for drying applications. Thus, the results of the present study imply that this novel idea has appreciable potential for commercialization with large-scale central air conditioning units in commercial complexes and industries where the magnitude of heat rejection will be multi-fold.

Echocardiographic evaluation of ventricular performance in VA-ECMO weaning: results from a observational multicentric prospective study

Abstract Funding Acknowledgements None. Background Although temporary mechanical circulatory support devices are increasingly used in the management of cardiogenic shock (CS), several open question regarding the kind of support and timing of institution/weaning remains open. Echocardiography is widely applied to drive the weaning process from VA-ECMO although there are no standardized protocols. Purpose We sought to evaluate the accuracy of echocardiographic indices in predicting successful weaning from VA-ECMO in CS patients. We tested total isovolumic time (tIVT), an index of ventricular performance(1,2), and longitudinal function (MAPSE) on top of the commonly used parameters (left ventricular ejection fraction, LVEF; E/e’ at mitral valve; left ventricular velocity time integral, LV VTI; TAPSE; right ventricular S’ at tissue Doppler imaging, RV S’). Methods Multicentric prospective study on adults receiving VA-ECMO due to refractory CS and/or cardiac arrest (CA) from 2012 to 2020. Echocardiography was performed at VA-ECMO placement and during the weaning trials. Waning trials were performed daily starting from 48 hours after VA-ECMO institution. A stepwise decrease of VA-ECMO blood flow was applied, until reaching 1 or 1.5 L/min. Successful weaning was defined as removal of VA-ECMO with no requirement for further MCS in the following 30 days. Results 76 patients were enrolled (23.8% female, 54.2±10.6 years-old), 52.6% due to CA. Median duration of VA-ECMO was 58 hours; 47 (61.8%) had intra-aortic balloon pump (IABP) inserted upfront. In-hospital mortality was 62.4% overall, 40% for CS without CA. 6 of the 32 weaned patients died in hospital for multiorgan failure due to septic shock. The baseline echocardiographic parameters associated with successful weaning were (Figure 1-A): stroke volume (SV) &amp;gt;13.2 ml (HR 4.12 [1.71-9.95], p 0.002), tIVT &amp;gt;23.6 min/sec (HR 0.14 [0.02-1.03], p 0.053), LV VTI &amp;gt;6.6 cm (HR 4.99 [1.94-12.87], p&amp;lt;0.001), MAPSE &amp;gt;6.15 mm (HR 4.42 [1.90-10.24], p 0.001), TAPSE &amp;gt;11 mm (HR 10.13 [1.37-7.02], p 0.023), RV S’ &amp;gt;7 cm (HR 5.40 [1.45-20.12], p 0.012). LVEF, E/e’ and S’ at mitral valve did not reach the statistical significance. Figure 1-B shows Kaplan-Meier analysis on echocardiographic indices collected during the last weaning trial; figure 2 details HR of all these parameters. Conclusions Echocardiography is pivotal in defining cardiac recovery and monitoring the weaning trial. Indices reflecting ventricular performance and delivered flow from LV were associated with weaning success both at VA-ECMO institution and throughout the weaning trials. Parameters reflecting ventricular activation and systo-diastolic interaction already demonstrated superiority in defining ventricular performance. Considering the known limitations of LVEF (HR, loading and LV dyssynchrony dependence), tIVT and MAPSE should be introduced in the standard evaluation in the acute setting.

An MCDA composite index of bank stability using CAMELS ratios and shannon entropy

AbstractThis study uses the multi-criteria decision-analysis (MCDA) approach to construct a composite performance index (CPI) directly from the CAMELS financial ratios. The CPI has several promising characteristics, such as (i) being an absolute measure of performance that allows for adding or removing data without affecting the existing scores; (ii) employing CAMELS ratios directly in its calculation without the need for normalization or imputation of positive values; (iii) employing the dynamic weighting system of data envelopment analysis (DEA); (iv) providing more robust insights on the Vietnamese banking system under the Shannon entropy approach; and (v) can be an alternative measure of bank stability, compared to the CAMELS ratings and z-scores. Based on a rich dataset of 45 Vietnamese banks spanning from 2002 to 2020, our findings suggest that the proposed CPI could offer an overall view consistent with other approaches for measuring banking sector performance and stability and identifying specific strengths and weaknesses of banks.

Bio-Inspired Intelligent Swarm Confrontation Algorithm for a Complex Urban Scenario

This paper considers the confrontation problem for two tank swarms of equal size and capability in a complex urban scenario. Based on the Unity platform (2022.3.20f1c1), the confrontation scenario is constructed featuring multiple crossing roads. Through the analysis of a substantial amount of biological data and wildlife videos regarding animal behavioral strategies during confrontations for hunting or food competition, two strategies are been utilized to design a novel bio-inspired intelligent swarm confrontation algorithm. The first one is the “fire concentration” strategy, which assigns a target for each tank in a way that the isolated opponent will be preferentially attacked with concentrated firepower. The second one is the “back and forth maneuver” strategy, which makes the tank tactically retreat after firing in order to avoid being hit when the shell is reloading. Two state-of-the-art swarm confrontation algorithms, namely the reinforcement learning algorithm and the assign nearest algorithm, are chosen as the opponents for the bio-inspired swarm confrontation algorithm proposed in this paper. Data of comprehensive confrontation tests show that the bio-inspired swarm confrontation algorithm has significant advantages over its opponents from the aspects of both win rate and efficiency. Moreover, we discuss how vital algorithm parameters would influence the performance indices.

Thermal design and experimental verification of the space ultraviolet wide field of view multi-channel scanning imager

In order to ensure the optimal imaging quality of the space ultraviolet wide field of view multi-channel scanning imager, it is imperative to conduct a comprehensive investigation into the thermal control system. First, we shall present the structure and performance index of the imager. The determination of the heat dissipation surface's position follows an analysis of the imager's exterior heat discharge. Subsequently, the thermal control design for every individual component of the imager is determined, considering the challenges associated with thermal management. The accuracy of the initial thermal design is verified by doing thermal simulation studies. Subsequently, the thermal equilibrium test was performed. The test results reveal that the temperature of the lens assembly varied between 20.0 °C and 25.6 °C, the horizontal bracket ranged from 19.7 °C to 21.7 °C, the vertical bracket exhibited temperatures between 11.2 °C and 15.4 °C, the U-frame experienced temperatures ranging from 15.1 °C to 17.4 °C, the motor showed temperatures between 6.6 °C and 26.3 °C, the detector recorded temperatures between 21.4 °C and 25.9 °C, and the high voltage module exhibited temperatures ranging from 8.9 °C to 19.9 °C. The temperature of each component is within the designated thermal control range. Extensive evidence has been presented to demonstrate the effectiveness and precision of thermal design.

Improved comprehensive adhesion performance of aggregate- recycled asphalt interface via incorporating steel slag

Steel slag, a typical industrial waste, reveals high alkalinity and abundant texture, endowing its excellent adhesion performance with asphalt and facilitating its implementation in recycled asphalt mixture. While few studies focused on the interaction mechanism and comprehensive adhesion performance of steel slag- recycled asphalt interface. Hence, this topic merits further exploration. In this study, the interface models of steel slag-asphalt were established and their interface parameters also were surveyed. And the comprehensive evaluation index of adhesion performance was explored by the improved radar chart. The experimental results elaborate that steel slag exhibits the larger surface energy of 46.69 mJ/m2 and higher percentage of dispersion component of 76.6 %. Recycled asphalt-steel slag demonstrates the greater adhesion work, the smaller exfoliated work and the larger adhesive destructive force than recycled asphalt-basalt, indicating its superior adhesion ability. Steel slag-asphalt molecule behaves the lower radial distribution function and larger interfacial bonding energy due to the dual provision of van der Waals force and electrostatic adsorption force. The exfoliated work in experiment and adhesion work in simulation presents a Pearson correlation coefficient of −0.683, resulting in their strong negative correlation. Steel slag-recycled asphalt interface with the higher comprehensive evaluation index of 0.9155 reveals the superior comprehensive adhesion performance than basalt- recycled asphalt.

Finite-time resilient control for uncertain periodic piecewise polynomial time-varying systems

This study explores the problem of finite-time resilient control for periodic piecewise polynomial time-varying systems in the face of parameter uncertainties, time-varying state delays and external disturbances. Particularly, the considered system is characterized by dividing the fundamental period of periodic systems into numerous subintervals, each of which can be expressed by using matrix polynomial functions. The foremost intention of this work is to lay out a resilient controller such that the resulting closed-loop system is finite-time bounded and satisfies a mixed [Formula: see text] and passivity performance index. Furthermore, by constructing a periodic piecewise time-varying Lyapunov–Krasovskii functional, a delay-dependent sufficient condition is established in line with Wiritinger’s inequality and matrix polynomial lemma to guarantee the needed outcomes of the system under study. Following this, the gain matrix of the devised controller can be calculated by solving the established constraints. As a final step, we conclude with a numerical example that validates the potential and importance of the theoretical discoveries and the developed control scheme.

Flood susceptibility modeling by integrating tree‐based regression with metaheuristic algorithm, BWO

AbstractFloods are becoming more widely acknowledged as a common occurrence of nature's dangers on a global scale. Although forecasting models primarily focus on timely warnings, models aimed at evaluating dangerous zones can play a vital role in shaping policies for adaptation, mitigation, and reducing the risk of disasters. Using machine learning techniques including hybrid black widow optimization (BWO) with XGBoost, LGBoost, and AdaBoost. We generate a flood susceptibility map for considered region of lower mahanadi basin (LMB). This study examines the effectiveness of these machine learning models in assessing and mapping flood susceptibility, while also providing suggestions for future research in this area. Flood susceptibility model was developed using 13 variables: Altitude, Aspect, Curvature, Distance from river, Drainage Density, Stream Power Index (SPI), Sediment Transport Index (STI), Rainfall intensity, Land Use Land Cover (LULC), Topographic Wetness Index (TWI), Terrain Roughness Index (TRI), Normalized Difference Vegetation Index (NDVI), and slope. Additionally, flood inventory data were incorporated into the model. Dataset was divided into a 70% portion for training model and a 30% portion for validating model. To assess the performance of the model, several evaluation metrics were employed, including receiver operating characteristic (ROC) curve and other performance indices. Evaluation of flood susceptibility mapping, using ROC curve method in combination with flood density yielded strong and reliable results for various models. BWO‐XGBoost achieved a score of 0.889, BWO‐LGBoost achieved a score of 0.937, and BWO‐ADABoost achieved a score of 0.904. These scores indicate effectiveness of these models in accurately predicting flood susceptibility in the study area. A comparison was made with commonly used methods in flood susceptibility assessment to evaluate the efficiency of proposed models. It was found that having a first‐class and enlightening database is crucial for accurately classifying flood types in flood susceptibility mapping. This aspect greatly contributes to improving the overall performance of the model. Among the evaluated methods, the hybrid model BWO‐LGBoost demonstrated better performance compared with others, indicating its effectiveness in accurately predicting flood susceptibility.

A decision-making approach on control techniques for an inverted pendulum based on, neuro-fuzzy, indirect adaptive and PID controllers

The operation of an inverted pendulum and its respective type of control are affected by the change of the values of its internal parameters. Changes with high uncertainty result in responses with undesirable outputs. In this work, a comparison is presented for the control of an inverted pendulum to determine the operation and characteristics of three types of control systems: Neuro-Fuzzy Control (NFC), Indirect Adaptive Control (IAC) and a Proportional Integral Derivative control (PID). The study considers several indices such as stabilization time, rise time, mean square error, overshoots, convergence, computational load, error, mathematical requirements, and performance indices for control systems. To demonstrate its operation, the controls are implemented in hardware, one for the NFC and another for the IAC under an Arduino UNO platform. The results indicate that the NFC and IAC controls do not generate a transient or impulse response, only a small delay and the rise and stabilization time are minimal. While PID presents a transient response and overshoot, as well as a stabilization time to reach the steady state response.

Experimental assessment of the energy performance of a renewable air-cooling unit based on a dew-point indirect evaporative cooler and a desiccant wheel

Given the escalating energy consumption in cities worldwide, it is crucial to investigate the utilization of sustainable technologies and renewable energy sources. The number of empirical studies on the energy performance of hybrid air-cooling systems is limited. Therefore, the objective of this work is to experimentally study the energy performance of a novel renewable air-cooling unit. This prototype is mainly composed of a desiccant wheel and a dew-point indirect evaporative cooler to independently control the temperature, humidity, and carbon dioxide levels of indoor air. 64 experimental tests are carried out to fit an empirical model of this renewable air-cooling unit, focusing on outlet air conditions and the coefficient of performance. In addition, several performance indices are developed for desiccant wheel and dew-point indirect evaporative cooler: (i) moisture removal capacity; (ii) moisture removal capacity per unit of electrical power-consumption; (iii) dew-point efficiency and (iv) cooling capacity of dew-point indirect evaporative cooler per unit of electrical power-consumption. The highest values of dehumidification capacity, sensible cooling capacity and coefficient of performance for this renewable air-cooling unit are achieved for the most severe outdoor air conditions, namely 19.02 kg·h−1, 21.49 kW and 11.0, respectively. This work can serve as a reference for research on the feasibility of hybrid air-cooling systems in the scenarios of heat events and climate change world.

Numerical Simulation Study on the Seismic Performance of Prefabricated Fiber-Reinforced Concrete Beam–Column Joints With Grouted Sleeve Connections

Based on the available experimental data, fiber models for four prefabricated fiber-reinforced concrete beam–column joint specimens with grouted sleeve connections are first developed in OpenSees software. Then, the simulated seismic performance of the specimens is compared with the experimental results. Finally, the effects of axial load ratio and shear-to-span ratio on the seismic performance of the specimens are further investigated numerically. The results indicate that Concrete02 material model and Reinforcing Steel material model can accurately simulate the constitutive relationship of concrete and reinforcing steel, respectively; the beam–column joint elements can accurately simulate different damage behaviors of the joint zone. Fiber-reinforced concrete can significantly improve the seismic performance of the specimens. The relative errors of the simulated seismic performance indexes are about 15%. It is recommended that the optimum value of shear-to-span ratio for prefabricated FRC BCJs is 2.0–2.5. The effect of axial load ratio on the seismic behavior of PBCJs-CM is very small, and can be negligible in the case that the prefabricated FRC BCJs has a moderate value of shear-to-span ratio. The fiber model developed in this article can provide a numerical simulation basis for subsequent studies of prefabricated fiber-reinforced concrete beam–column joint specimens with grouted sleeve connections.

Experimental study on co-combustion of domestic garbage and sewage sludge: Evaluation of synergistic effect and thermo-kinetic behavior

A persistent increase in domestic garbage (DG) has become a significant worldwide issue due to its negative impact on the ecosystem. The co-combustion way of DG and sewage sludge (SS) in a garbage incineration plant has been deemed a viable option. The study aims to quantify co-combustion behaviors, interaction effects, and thermo-kinetic properties between DG and SS at isothermal conditions by a thermogravimetric analyzer. The results showed that co-combustion of DG with 20 % SS could boost the combustion performance indices, and exhibit the synergistic effect. In addition, at the various SS blending ratios (10, 20 and 35 %) under an air atmosphere, combustion performance indices gradually decreased with an increased SS blending ratio but the synergistic effects were inhibited with a 35 % SS blending ratio. Coat-Redfern method was used to determine the combustion kinetics and thermodynamic properties. The apparent activation energy in the DG-SS (80 %/20 %) blend exhibited a non-linear relationship but increased proportionally with higher SS blending ratio. The lowest activation energy (34.70 kJ/mol) was obtained at the DG-SS (90 %/10 %) blend. The results suggest that the co-combustion of DG and SS can improve the overall combustion performance with an optimal blending ratio of 20 % SS for the co-combustion application.