Daily Output Research Articles

Hydro–Wind–PV–Integrated Operation Optimization and Ultra-Short-Term HESS Configuration

In order to address the challenges associated with optimizing multi-timescale operations and allocating ultra-short-term energy storage for HWP integration, this study takes into account both the economic and reliability aspects of the HWP integration base. It proposes a model for optimizing operations and allocating energy storage capacity, achieving optimization across long-term, short-term, and ultra-short-term operations for an MECB. Initially, operation optimization is implemented for an entire group of terraced hydropower plants by regulating them with annual regulating capabilities on a long-term timescale. The objectives are to maximize the daily average minimum output and annual power generation. Subsequently, short-term operation optimization focuses on maximizing HWP power feed-in, minimizing new energy power curtailment, and reducing residual load standard deviation while ensuring the guaranteed output optimization results for the long term. Finally, to mitigate ultra-short-term fluctuations in new energy, a HESS with specified capacity and power is configured with the goal of minimizing comprehensive costs. Additionally, to address the challenge of smoothing negative fluctuations, which is hindered by charging and discharging efficiency limitations, a variable baseline is introduced, deviating from the conventional 0 MW baseline. A simulation study based on data from the hydro–wind–PV hybrid project in the Beipanjiang River Basin, China, demonstrates the following: (1) after long-term system optimization, the total power generation capacity of the system increases by 9.68%, while the peak-to-valley difference in output is significantly reduced; (2) short-term system optimization significantly reduces both the average variance in residual loads and the amount of power curtailed over five representative days; (3) the system incorporates 398.62 MWh of lithium-ion battery storage with a power of 412.47 MW and 51.09 MWh of supercapacitor storage with a power of 223.32 MW, which, together, completely smooth out the ultra-short-term fluctuations in new energy output.

Fine-grained simulation model for PV power output interval based on two-stage scenario clustering and dual-ensemble compatible learning

Photovoltaic (PV) power simulation is indispensable for the planning and operation of renewable-rich power systems. Among various simulation methods, data-driven indirect simulation methods are the most efficient, primarily involving scenario extraction and power output generation. Typical scenario extraction methods often feature coarse characterizations, which also cannot be expressed by traditional power output generation models lacking the ability of quantifying the uncertainty of the output results. This paper proposes a fine-grained simulation model for PV power output interval, i.e., upper bound and lower bound, based on two-stage clustering of multiple typical scenarios and dual-ensemble compatible learning. The first stage of scenario extraction, considering the impact of total daily irradiance on PV output, employs a line distance index for preliminary scenario division of daily PV output. These scenarios are further divided into five characteristic scenarios with an angular distance index considering the impact of intra-day irradiance variations on power output. PV power output interval is generated from dual-ensemble compatible learning including Stacking and Bagging, which are adaptively selected with a Bias-Variance Selection Index (BS) calculated using the value of scenario characteristics. Stacking and Bagging are driven by three neural network base learners with Bayesian layers, which can output the lower bound and upper bound with confidence at a certain level, thus quantifying the uncertainty of the result accurately. The actual data of Daxing and Gangjialing power stations are used in case study. Results form case study show that compared with the existing methods, the proposed method can improve the Power Coverage Rate (PCR) and Average Power Simulation Accuracy (APA) of uncertainty simulation results by 27.44% and 5.39%, respectively. Meanwhile, the Average Daily Maximum Power Simulation Accuracy (AMPA) is similar to that of existing methods.

Urinary output of very low birth weight infants during the first weeks of life

Introduction: Daily urinary output (UOP) serves as important tool to identify acute kidney injury (AKI) in preterm infants. However, reference values for UOP, especially stratified for gestational age, are missing. Methods: This retrospective single-center study assessed UOP during the first 28 days of life in 128 very low birth weight (VLBW) infants. Results: VLBW infants exhibit a highly dynamic daily UOP profile in the first 28 days of life with a maximum at day 12 with 4.78 ml/kg bodyweight/h. In the subcohort of 64 extremely low gestational age neonates (ELGAN), the highest UOP is measured during the second week of life. Infants born before 24 weeks of gestation have significantly higher UOP than more mature infants. Conclusion: UOP is dynamic in the postnatal period and differs significantly between gestational age cohorts in the subgroup of ELGANs. These data might point to an adaption of the UOP threshold for neonatal AKI in preterm infants.

Influence of Horizontal Model Resolution on the Horizontal Scale of Extreme Precipitation Events.

A fundamental characteristic of extreme precipitation events (EPEs) is their horizontal scale. This horizontal scale can influence the intensity of an EPE through its effect on the timescale of an EPE as well as its effect on the strength of convective feedbacks. Thus, to have confidence in future projections of extreme precipitation, the horizontal scales of EPEs in global climate models (GCMs) should be evaluated. Analyzing daily output from 27 models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6), including 13 models participating in the High Resolution Model Intercomparison Project (HighResMIP), we computed the horizontal scales of EPEs and extreme ascent for annual maximum EPEs during 1981-2000. We found that the horizontal scales of both EPEs and the associated ascending motion are resolution-dependent: for a factor of seven increase in horizontal resolution, the horizontal scale decreases by a factor of approximately two to five, with higher sensitivity in the tropics than in the midlatitudes. Further analysis in the southern hemisphere midlatitudes reveals that this resolution dependence results from precipitation during the simulated EPEs that is almost entirely resolved rather than parameterized. However, the EPEs are not simply grid box storms, and analysis of the horizontal scales of geopotential anomalies suggests that the planetary-scale dynamics in GCMs is not resolution-dependent. Thus, the dominance of resolved precipitation during EPEs is more likely due to convection on the model grid or formation of strong, poorly resolved fronts, and additional work is needed to explore these possibilities and find a remedy for this resolution dependence.

Improving Workers' Performance in Small Firms: A Randomized Experiment on Goal Setting in Ghana

Abstract We report the results of a cost-effective intervention to improve workers' performance in small cassava processing firms in Ghana. We train workers to track their daily output and then randomly assign a sub-sample to set daily production goals. Achieving or missing a goal does not carry monetary consequences. Goal setting increases workers' output by 16%, their productivity by 8% and the average product of labor in firms by 13%. Goal setting is particularly effective for piece-rate workers, increasing their output by 32% and productivity by 24%. While not conclusive, evidence suggests that goals serve as a self-regulation device.

Design, techno-economic evaluation, and experimental testing of grid connected rooftop solar photovoltaic systems for commercial buildings

This study aims to investigate the potential of rooftop solar photovoltaic systems for commercial buildings. Helio-Scope software is utilized to perform simulations to determine the ideal rooftop area for photovoltaic panels. The efficiency of photovoltaic systems is impacted by the shading effects of photovoltaic modules installed in parallel rows. To enhance energy output, the optimal distance between rows is determined, and it is found that 5-feet inter-row spacing provides the best results. The simulation results indicate that with 5-feet inter-row spacing, photovoltaic system has an energy generation of 371.6 MWh, specific yield of 1508.0 kWh/kWp, performance ratio of 82.1%, solar access rate of 98.9%, total solar resource fraction of 96.3% and a total irradiance of 1655.9 kWh/m2. The annual nameplate energy is 425.1 MWh, output energy at irradiance levels is 423.1 MWh, optimal DC output is 378.5 MWh, inverter output is 373.5 MWh, and total energy delivered to the national power grid is 371.6 MWh. The average daily DC inverter input power is 158881.5110 W and the average daily AC inverter output power is 152231.6311 W, showing an inverter efficiency of approximately 95.93%. Moreover, detailed testing of the installed PV system is performed on-site to make sure that equipment’s performance guarantees are achieved, the system is properly installed and its configuration is suitable for commercial operations. The maximum daily output energy generation of an installed photovoltaic (PV) system is 1.33 MWh, and its average energy generation is 1.09 MWh. The voltage of all strings is within the rated range of the inverter, with a maximum voltage of 835 V and a minimum of 698 V, as tested by PV string open-circuit voltage. The inverter efficiency test is also performed, with a maximum efficiency of 98.83% and fill factors ranging from 81.37% to 82.34%. The payback period of a photovoltaic system is 4.22 years and LCOE is 0.0229$/kWh. PV system saved 215569.818 metric tons of CO2 in the first year and a total of approximately 5068976.99 metric tons in 25 years.

Efisiensi Penggunaan CBC Calculator sebagai Alat Bantu Pengukuran Produktivitas Metode Crew Balance Chart

Work productivity in construction project operations is often measured using non-scientific methods due to the relatively short time required. Productivity is typically calculated based on daily production output, which is measured in the afternoon. One scientific method for measuring productivity is the Crew Balance Chart (CBC). This study aims to evaluate the efficiency that can be achieved through an Android-based application specifically designed to streamline data processing and reduce measurement time. The method used is a comparative analysis of productivity measurement duration by comparing standard CBC methods with the tools, using a tower crane operation as a case study. The findings reveal an efficiency increase of 142.1%. The use of the Android-based application reduced measurement duration by 1,11 hours, from 3,76 hours to 2,64 hours. It is important to note that the application assists only in the data processing stage, while data collection and analysis continue to follow standard CBC procedures.

Design and performance characteristics of single-axis tracking dual confocal low-magnification parabolic trough CPV system

With the rapid increase of PV module utilization, the environmental pollution associated with waste photovoltaic (PV) module and its recycling is of concern. This paper proposes a concentrating photovoltaic (CPV) system to reduce the use of PV module. The cross-confocal method is employed for the concentrator to eliminate central dark streaks. In optical simulation, a theoretical uniformity index of 0.0466 and a theoretical optical efficiency of 89.87 % were achieved. When the distance between the rotational axis and the center of gravity is less than 125.8 mm, the system can withstand winds of 20.4 m/s. The temperature range of the PV, obtained from finite element analysis, is from 295.71 K to 363.13 K. With the requirements of the relative optical efficiency of over 90 % and the uniformity index of less 0.5, the system has a dimensional translation tolerance of approximately ±10 mm, a dimensional rotation tolerance of about 5°, and a tracking angle tolerance of about 1°. The actual daily average output current of this system has increased by 100.91 %. The ratio between the increase ratio of output current and the theoretical concentration ratio is 83.4 %. The system demonstrates excellent optical performance and system tolerance.

A high-performance all-day vertical thermoelectric generator based on a double-sided reflective structure

Harvesting environmental energy sources is crucial for achieving renewable energy generation and net-zero emissions. However, ensuring uninterrupted electricity generation from environmental energy sources remains challenging. In this study, we present a simple, compact, and expandable all-day vertical passive thermoelectric generator (V-TEG) with a double-sided reflective structure that simultaneously harnesses solar and space cold energy. Outdoor experimental measurements, combined with finite element simulation analysis, revealed that the optimal angles of the solar reflector relative to the TEG range from 30° to 50°. Additionally, the TEG placed in the north–south orientation was found to enhance its daytime performance. The use of low-cost black paint combined with the solar reflector achieved equivalent spectral selectivity, effectively minimizing the infrared heat loss of the hot end of the TEG. During a 48-h outdoor test, the V-TEG achieved an average daytime power of 112.00 mW/m2 and a peak of 363.42 mW/m2. Comparative experiments demonstrated that the V-TEG outperformed horizontally placed TEG during the daytime. Furthermore, scaling the system by connecting three TEGs in series significantly increased the daily power output. This compact V- TEG system offers a promising solution for long-term power generation in low-power sensors and off-grid communities, supporting renewable energy and carbon neutrality goals.

Role of aminophylline in prevention of acute kidney injury in term neonates with severe perinatal asphyxia: a randomized open-label controlled trial.

Acute kidney injury (AKI) is one of the frequently observed complications in neonates with severe perinatal asphyxia. The efficacy of aminophylline in preventing or alleviating renal dysfunction in these neonates remains controversial. The current study aimed to explore whether treatment with aminophylline as adjunctive therapy is superior to standard care alone in preventing AKI in severely asphyxiated term neonates and to delineate the changes in other renal parameters. In this open-label randomized clinical trial, term neonates with severe asphyxia (n = 41) received a 5 mg/kg intravenous dose of aminophylline within the first hour after birth, in addition to standard care for birth asphyxia. The control group (n = 40) received standard care alone. Their daily urine output, weight, serum creatinine, renal functional status, and complications during the first 5 days of life were monitored and compared. The statistical package for social sciences version 25 was used for analysis. Approximately 24.39% of neonates in the aminophylline group developed AKI, compared to 35.0% in the control group (P = .088). Although urine output was generally higher in aminophylline-treated newborns than in the control group, this increase was not statistically significant (P > .05), with the most notable differences observed on the second and third postnatal days. Also, the changes in plasma creatinine levels between the two groups during this time were not statistically significant. Administering a single dose of aminophylline (5 mg/kg) within the first hour of life to severely asphyxiated term neonates might temporarily enhance urine output, but does not reduce the overall incidence of AKI.

Experimental investigation of developed solar still using vertical backside wick with circulation tactics

The primary obstacle to the widespread use of solar stills is their low productivity; therefore, the primary goal of this study is to increase solar still productivity by utilizing fabric as an evaporation surface on the still's upright side. Two monoclinic solar stills were built and used in the appropriate meteorological circumstances (latitude 35º.25˝, longitude 43º.53˝). Four water levels of 1, 2, 3, and 4 cm were utilized to study the impact of water level on the daily output and effectiveness of solar stills, but no improvements were observed. A cotton cloth was hung on the upright side of the still to increase the evaporation surface area. The empirical findings demonstrated that solar still yield and daily efficiency were highest at a depth of 1 cm, where yield reached 5760 mL/m2 and daily efficiency was 44 %. The still's daily productivity increased with cloth, reaching around 6650 mL/m2 and a daily efficiency of 55.3 % at a water level of 1 cm. By using cloth, the solar still's daily production increased by 40 %. The traditional and modified solar stills cost 0.015 $ and 0.014 $, respectively, to produce one liter of distilled water.

Short communication: Dairy Victory™ Platform: A Novel Benchmarking Platform to Empower Economic Decisions on Dairy Farms.

In the face of diminishing economic margins, dairy farmers globally are compelled to maintain economic competitiveness. Benchmarking emerges as a strategic tool to establish new, achievable improvement objectives that balance ambition with practicality. This typically requires integrating diverse data sources such as feed, milk production, diet, and market prices. However, many farms lack essential, cow-level data like daily milk output and milk income over feed cost (IOFC), which hampers economic performance visibility and informed decision-making. To address this challenge, we introduce “Dairy Victory™ platform (DVP)” a novel cloud-based benchmarking platform designed to simplify complex analyses. The DVP uniquely calculates zootechnical and economic key performance indicators (KPIs) at the cow and herd levels and benchmarks these against a dynamically selected cohort of farms, facilitating comparisons across various farm sizes, and milk production levels. The primary objective of this paper is to demonstrate the utility of DVP as a decision-making tool in supporting farmers and consultants with both operational and strategic decisions. It emphasizes leveraging benchmarking information to enhance decision-making processes, thereby highlighting the significant value that DVP brings to farmers, consultants, and dairy farm stakeholders. Our study analyzed data from 712 farms from December 2023, focusing on several KPIs, such as milk production, milk quality, feed efficiency, and IOFC using Dairy Herd Improvement (DHI) records. This approach showcases DV's ability to utilize minimal data inputs for detailed analysis, leveraging peer performance to set desirable and/or achievable goals. We present a case study demonstrating how the DVP platform can guide dairy farms using anonymized peer data. This approach enables users to potentially improve their IOFC by up to 35%. Our findings highlight DVP's potential as a powerful tool for generating insightful analyses, simulations, and recommendations, primarily from test-day data, but also integrated with market and estimated data. This supports more strategic decision-making in dairy management, including automatic goal-setting based on peer performance.

Two Perspectives on Amplified Warming over Tropical Land Examined in CMIP6 Models

Abstract Climate change projections show amplified warming associated with dry conditions over tropical land. We compare two perspectives explaining this amplified warming: one based on tropical atmospheric dynamics and the other focusing on soil moisture and surface fluxes. We first compare the full spatiotemporal distribution of changes in key variables in the two perspectives under a quadrupling of CO2 using daily output from the CMIP6 simulations. Both perspectives center around the partitioning of the total energy/energy flux into the temperature and humidity components. We examine the contribution of this temperature/humidity partitioning in the base climate and its change under warming to rising temperatures by deriving a diagnostic linearized perturbation model that relates the magnitude of warming to 1) changes in the total energy/energy flux, 2) the base-climate temperature/humidity partitioning, and 3) changes in the partitioning under warming. We show that the spatiotemporal structure of warming in CMIP6 models is well predicted by the inverse of the base-climate partition factor, which we term the base-climate sensitivity: conditions that are drier in the base climate have a higher base-climate sensitivity and experience more warming. On top of this relationship, changes in the partition factor under intermediate (between wet and dry) surface conditions further enhance or dampen the warming. We discuss the mechanistic link between the two perspectives by illustrating the strong relationships between lower-tropospheric temperature lapse rates, a key variable for the atmospheric perspective, and surface fluxes, a key component of the land surface perspective. Significance Statement Understanding what conditions give rise to the largest magnitude of warming in response to rising CO2 concentrations is not only scientifically important but also critical from a climate impact standpoint. Two main perspectives, one focusing on atmospheric dynamics and the other focusing on land surface processes, have been proposed to explain the stronger warming associated with drier conditions in the tropics. Here, we compare and contrast these two perspectives. We demonstrate that amplified warming in CMIP6 models can largely be predicted from base-climate dryness alone in both perspectives but is further modified based on changes in the partitioning of energy between temperature and moisture. We highlight the spatiotemporal conditions where assumptions in the two perspectives hold and where deviations occur within CMIP6 climate models.

Hypothalamic-pituitary-adrenal axis function in the offspring of parents with bipolar disorder and the impact of the family environment: A pilot study of the Reducing Unwanted Stress in the Home (RUSH) prevention program

BackgroundThe home environment of offspring of parents with bipolar disorder (OBD) has been characterized by high levels of stress and disorganization, which may impact development of the hypothalamic-pituitary-adrenal (HPA) axis and their subsequent risk for affective disorders. The present study examined the effects of a family-based preventative intervention on the OBD’s HPA axis functioning and whether intervention-related changes in the home environment might have driven change in the HPA axis. MethodsFifty-five children (6–11 years) were recruited from families having a parent with bipolar disorder (n=26) or families having two parents with no current mental disorders (n=29). Only those families with a parent having bipolar disorder participated in the preventative intervention. Both groups completed assessments at baseline, post-prevention, 3-, and 6-months post-prevention. At each assessment, family organization, control, cohesion, conflict, and expressiveness, in addition to childhood internalizing problems, were measured, and offspring saliva samples were collected across two consecutive days. ResultsHierarchical Linear Modelling found no significant differences in HPA axis functioning between groups at baseline or across time. Improvements in family organization, however, were associated with elevations in participants’ cortisol awakening response (CAR; p =.004) and total daily output (p =.023), and a steepening of their diurnal slope (p =.003) across time. Similar findings were obtained for family cohesion with respect to CAR (p <.001) and, to a lesser degree, diurnal slope (p =.064). DiscussionHPA axis functioning did not differ between the OBD and healthy controls at baseline or in response to the preventative intervention. However, intervention-related improvements in family organization and, to a lesser degree, cohesion, were associated with adaptive changes in HPA functioning over time.

Configuration optimization of PV array for stratospheric airship under nonuniform radiation condition

The nonuniform solar irradiation on the stratospheric airship surface leads to overlooked mismatch losses in photovoltaic (PV) array. Proper configuration for PV array is crucial but frequently neglected in airship energy system research. In this paper, a mathematical model coupled with the layout of PV array on airship surface, radiation model, electrical model and energy balance model is established. The deployment of PV pack based on the distribution characteristics of solar radiation on airships surface is analyzed. Three maximum power point tracking configurations for the PV array are investigated in detail. The results indicate that mounting PV pack in axial series on stratospheric airships leads to higher power output compared to parallel-connected deployment, PV packs on stratospheric airships exhibit significant output power differences along the circumferential direction and minor differences along the axial direction, the peak of daily maximum output difference ratio is merely 0.4 % between the PV array under the distributed maximum power point tracking (DMPPT) and the partial distributed global maximum point tracking (PDMPPT) configuration, and PDMPPT configuration needs much fewer module, it emerges as the optimal choice for stratospheric airship PV array. This investigation can provide references for the further PV array configuration optimization under nonuniform radiation condition.

Mission-oriented dynamic reconfiguration of airborne photovoltaic array based on multidisciplinary model

The solar-powered stratospheric airship is demonstrated overwhelming superiority because of affordable cost, recyclable material and low carbon emission. Progress has been made in the schemes of energy system consisting of curved photovoltaic array, storage, and energy management devices. However, research on various flight conditions and the resulting presence of non-uniform irradiance on the airborne solar array is rare. Moreover, the methods to reduce the power losses of on-board solar array are not investigated. This paper proposed a dynamic reconfiguration method to improve the output performance of on-board solar array in different mission conditions. The partial shading conditions of airborne and ground-based solar arrays are compared. The multiple traveling salesman problem with solar array is introduced. The Simulated annealing algorithm is adopted. The real-time optimization of solar array is obtained with the dynamic reconfiguration method according to the operating condition consisting of various parameters. The results show the proposed method effectively improves the output power of solar array compared with common total-cross-tied connections. The improvements of daily output energy of the airborne array are more than 13.7 %. The work provides a conducive reference for realizing the utilization prospect of solar energy system on aerial vehicles in a low carbon future.

Performance Analysis of a 50 MW Solar PV Installation at BUI Power Authority: A Comparative Study between Sunny and Overcast Days

Ghana, being blessed with abundant solar resources, has strategically invested in solar photovoltaic (PV) technologies to diversify its energy mix and reduce the environmental impacts of traditional energy technologies. The 50 MW solar PV installation by the Bui Power Authority (BPA) exemplifies the nation’s dedication to utilizing clean energy for sustainable growth. This study seeks to close the knowledge gap by providing a detailed analysis of the system’s performance under different weather conditions, particularly on days with abundant sunshine and those with cloudy skies. The research consists of one year’s worth of monitoring data for the climatic conditions at the facility and AC energy output fed into the grid. These data were used to analyze PV performance on each month’s sunniest and cloudiest days. The goal is to aid in predicting the system’s output over the next 365 days based on the system design and weather forecast and identify opportunities for system optimization to improve grid dependability. The results show that the total amount of AC energy output fed into the grid each month on the sunniest day varies between 229.3 MWh in December and 278.0 MWh in November, while the total amount of AC energy output fed into the grid each month on the cloudiest day varies between 16.1 MWh in August and 192.8 MWh in February. Also, the percentage variation in energy produced between the sunniest and cloudiest days within a month ranges from 16.9% (December) to 94.1% (August). The reference and system yield analyses showed that the PV plant has a high conversion efficiency of 91.3%; however, only the sunniest and overcast days had an efficiency of 38% and 92%, respectively. The BPA plant’s performance can be enhanced by using this analysis to identify erratic power generation on sunny days and schedule timely maintenance to keep the plant’s performance from deteriorating. Optimizing a solar PV system’s design, installation, and operation can significantly improve its AC energy output, performance ratio, and capacity factor on sunny and cloudy days. The study reveals the necessity of hydropower backup during cloudy days, enabling BPA to calculate the required hydropower for a consistent grid supply. Being able to predict the daily output of the system allows BPA to optimize dispatch strategies and determine the most efficient mix of solar and hydropower. It also assists BPA in identifying areas of the solar facility that require optimization to improve grid reliability.

The way out for urban household solid waste classification in China: From the perspective of multi-agent based behavior simulation

Rapid industrialization and urbanization drive China's massive urban household solid waste (HSW) generation. Classification and resource recycling of HSW is an effective way to address the “garbage-sieged city” dilemma and promote “urban mineral resources” exploitation. Despite efforts since 2000, HSW sorting and recycling remain at 30%. This study develops a multi-agent based behavior simulation model for HSW classification and recycling, incorporating the interactions and decision-making of key agents, including residents, enterprises, and the government. Taking Suzhou, China as a case study, field surveys were conducted, and behavioral decision-making functions were constructed to simulate micro-behavioral responses and macro-system evolution under different policy incentives, and to predict the implementation effect of domestic waste management approaches, provides the basis for decision-making. The results demonstrate that a combination of waste metering charges, recycling subsidies, and enhanced education program can effectively regulate agent behavior and optimize the system. One year after the implementation of the simulation, the number of “unclassification” residents has dropped from 1.85 million to 250,000 decreased by 86%; the number of “classification deposition” residents has declined from 1.28 million to 1.08 million, reduced by 16%; the number of “selling after classification” residents has risen from 1.05 million to 2.81 million, increased by 63%; the daily waste output per capita has decreased from 1.21 kg to 1.04 kg, reduced by 14%; the recovery rate of resources has been raised from 33.4% to 66.5%. The implementation effects of other policy scenarios are ranked as follows: the metering charge > the recycling subsides > the enhanced education program. The findings provide a basis for decision-making in HSW management. Concerning the metering charge and the recycling subsidies, they can benefit positive interactions encouraged by such economic stimulus. At the same time, it is suggested to strengthen classification and recycling infrastructure, and push forward the integration of HSW classification recycling.

Novel Workstation Module and Method for Automatic Blanking of Surgical Forceps

During the manufacturing of surgical forceps, the flashes of the blanks need to be removed. Manual production has problems such as high labor intensity, low efficiency, and high-risk factors. To solve this problem and realize fully automatic resection, a novel modular workstation was designed and a corresponding process method was proposed. The workstation adopts robots, non-standard automation equipment, and image recognition technology instead of manual loading and blanking, but the blank storage still needs to be performed manually. The critical components were selected according to the workstation design scheme and process method, and the control system design was completed. The reliability of the separation unit was studied through a test platform, and the failure problem caused by uneven force was solved using a blank locking device, which showed that the separation success rate was stabilized at 100%. The detection speed of the image recognition system can reach 100 ms/piece, and the product qualification rate can reach 95.7%. The advantages of the workstation in terms of output and productivity were further analyzed by comparing it to manual production, where the average daily output increased by 12.5% (4500 pieces). In addition, the results of long-term test experiments and power consumption comparison tests showed that the workstations are highly stable and consume little additional power.

Performance analysis of an SPD integrated with a stepped pyramid solar still: experimental study

AbstractWater scarcity poses a major challenge for the next generation. Additionally, increasing agricultural and industrial activities are creating an unprecedented demand for freshwater supplies throughout Egypt. The Nile River serves as Egypt’s primary water source, accounting for 69.4% of the total water resources. Moreover, Egypt's annual share of water has decreased to approximately 500 m3 per person because of the completion of the Renaissance dam in Ethiopia and the rapid increase in population growth. Solar distillation has been presented as a long-term and promising method for producing edible drinkable water. The present research goal is to increase the daily freshwater output from a stepped pyramid solar still (SPSS) by coupling with a solar parabolic dish (SPD). The proposed system consists of a conventional pyramid solar still (CPSS) and a modified pyramid solar still (MPSS). The main components of an MPSS include an SPSS, a PV panel, an SPD with a spiral coil, a circulating pump, and an Arduino Mega Unit. The developed system was designed, fabricated, and verified from July to August 2023 at the Faculty Engineering, South Valley University. The results of the experiments indicated that the daily productivity of freshwater from MPSS was greater than that from CPSS and reached 6038 and 2612 mL/day, respectively, with an increase in the daily yield of 131%. The peak energy efficiency is 56% for the MPSS and 24% for the CPSS. The peak exergy efficiency is 4.26% for the MPSS and 3.79% for the CPSS. Additionally, the cost analysis of the suggested system revealed that the estimated cost per liter of the proposed system is 0.01635 USD/L.