Improve System Efficiency Research Articles

Heat transfer analysis of ternary hybrid Williamson nanofluids with gyrotactic microorganisms across stretching surfaces: Local non-similarity method

Managing and controlling energy amidst rapid industrial and technological advancements pose significant challenges. Enhanced heat transfer processes, like free convection in solar panels and nuclear power plants, offer potential to reduce energy consumption and improve system efficiency. Understanding elements such as magnetic fields, thermal radiation, and nanoparticle morphology can optimize fluid dynamics and heat transfer across various domains including energy, aerospace, and nuclear power. This study aims to develop a two-dimensional Williamson fluid model with ternary hybrid nanofluids and gyrotactic microorganisms to deepen our understanding of heat transfer. Methodological enhancements include integrating viscous dissipation formulations and adopting the Rosseland approximation to address radiation effects accurately. By leveraging non-similarity transformations, equations are rendered nondimensional for efficient numerical solutions using MAT LAB. Graphical overviews and tables aid in comprehending key factors for practical applications and engineering analyses.

An Improved Zero-Flowrate Switching Control Method to Reduce Switching Losses in a Hydraulic Actuator

Hydraulic switching actuators are high-efficiency, fast response, and low-cost solutions for hydraulic control systems. One of the challenging problems is throttling losses during valve transitions. Previously, the authors proposed a zero-flowrate switching method to reduce the throttling energy loss of the switching valve, where a hydraulic resonator is applied to make the flowrates through the lines approaching zero before the valves are switched off. The major challenge of this approach is fast switching valves whose transition times are less than 2 ms. In this paper, an improved zero-flowrate switching method is presented. It utilizes the capacity with independent inlet/outlet ports to regulate flowrates through the lines. Models of capacity applied in a simple line with different pressure signals are developed to explore characteristics of the capacity, based on which a complete actuation system is developed. In the complete model, resistance and inductance are optimized to achieve the desired flowrate response. The improved zero-flowrate switching method reduces throttling energy losses by 99.945% compared to a hard switching system. The simulation results demonstrated that the improved zero-flowrate switching method performs as expected in the design condition. A capacity with proper volume is able to regulate flowrates through all the lines to zero, with the help of appropriate resistance and inductance. Compared to the previous zero-flowrate switching method, the novel strategy allows slower switching valves applied in hydraulic actuation systems and achieves better efficiency performance. This research paves a new avenue for reducing throttling energy losses and improves system efficiency in hydraulic switching actuators, as well as most of the hydraulic switch-mode circuits.

Advanced efficient energy management strategy based on state machine control for multi-sources PV-PEMFC-batteries system

This article offers a PV-PEMFC-batteries energy management strategy (EMS) that aims to meet the following goals: keep the DC link steady at the standard value, increase battery lifespan, and meet power demand. The suggested multi-source renewable system (MSRS) is made to meet load demand while using extra power to fill batteries. The major energy source for the MSRS is photovoltaic, and fuzzy logic MPPT is used to guarantee that the PV operates at optimal efficiency under a variety of irradiation conditions. The suggested state machine control consists of 15 steps. It prioritizes the proton exchange membrane fuel cell (PEMFC) as a secondary source for charging the battery when power is abundant and the state of charge (SOC) is low. The MSRS is made feasible by meticulously coordinating control and power management. The MSRS is made achievable by carefully orchestrated control and electricity management. The efficacy of the proposed system was evaluated under different solar irradiance and load conditions. The study demonstrates that implementing the SMC led to an average improvement of 2.3% in the overall efficiency of the system when compared to conventional control techniques. The maximum efficiency was observed when the system was operating under high load conditions, specifically when the state of charge (SOC) was greater than the maximum state of charge (SOCmax). The average efficiency achieved under these conditions was 97.2%. In addition, the MSRS successfully maintained power supply to the load for long durations, achieving an average sustained power of 96.5% over a period of 7.5 s. The validity of the modeling and management techniques mentioned in this study are confirmed by simulation results utilizing the MATLAB/Simulink (version: 2016, link: https://in.mathworks.com/products/simulink.html) software tools. These findings show that the proposed SMC is effective at managing energy resources in MSRS, resulting in improved system efficiency and reliability.

Kinematic and Dynamic Analysis of Eccentric Balanced Positive Torque Pumping Unit

Beam pumping units have numerous energy transfer links, significant net torque fluctuations and negative net torque in gear boxes, which lead to a high installed power and low system efficiency. In order to improve the efficiency of the pumping unit, in this paper, an eccentric balanced positive torque pump unit was designed based on the principle of eccentric balance that is small in size and adopts a flexible energy transfer system instead of a rigid structure to significantly reduce the energy transfer link. The kinematics and dynamics of the eccentric balanced positive torque pumping unit were analyzed and the ability to operate with positive torque over the entire cycle was verified using theoretical computations. And the results of the theoretical calculation were verified by using the virtual prototype simulation and analysis software ADAMS (Automatic Dynamic Analysis of Mechanical Systems); the pumping unit was optimized for relevant parameters such as the balance crank angle λ and the counterweight center of mass offset angle δ. Indoor testing and comparative field application have demonstrated that the installed power has been reduced by 80%, the weight of the entire prototype has decreased by 25% and the system efficiency has reached 24.3%. Additionally, electricity savings of over 50% have been achieved. These results indicate that the pumping unit has been designed correctly, has high reliability and has significantly improved system efficiency while also providing an obvious energy-saving effect.

Examining the Advantages, Limitations, Opportunities, and Challenges of AI Implementation in Libraries

Libraries will benefit greatly from the incorporation of artificial intelligence (AI), but they will also face substantial hurdles. It is therefore essential to carry out a thorough SWOT analysis that assesses the organization's opportunities, threats, weaknesses, and strengths. This abstract explores the potential uses, hazards, restrictions, and advantages of artificial intelligence in library environments. The study intends to provide useful insights into the strategic factors that libraries must take into account while implementing AI technologies by carefully examining these aspects.The study attention to the challenging terrain of integrating AI in libraries and stresses the significance of taking a comprehensive approach to fully utilize its potential while managing related dangers. Important tactics include improving system efficiency and tackling issues with algorithmic bias and privacy.Essentially, the goal of this study is to clarify the many ways that AI is being used in libraries. It emphasizes how important it is for libraries to thoroughly consider the effects of implementing AI and to create solid plans to maximize its benefits while avoiding any negative effects. By doing this, libraries can ensure responsible and ethical implementation processes while simultaneously positioning themselves to take advantage of the revolutionary prospects presented by AI.

Transforming Rural Governance through Enhanced Communication Strategies for Global Impact

This study explores the implementation challenges of a Website-Based Village Information System in Dukuhsari Village Government, focusing on communication, resource allocation, disposition, and bureaucratic structure. Through qualitative methods including interviews and observation, the study reveals gaps in communication and resource management, impacting the system's effectiveness. The findings emphasize the need for improved communication strategies, consistent training, and ongoing support to optimize the system's utility and enhance public service delivery in Dukuhsari Village. Highlight: Challenges in Village Information System Implementation: Communication and resource allocation. Improving System Efficiency: Enhanced communication strategies and consistent training. Impact on Governance: Transparency and accessibility in rural service delivery. Keyword: Village Information System, Implementation Challenges, Communication, Resource Allocation, Public Service Delivery

Research Progress on Nonlinear Modeling of Electro-Hydraulic Servo Systems and Innovative Applications of Control Strategies

Abstract: In various specific application domains, electro-hydraulic servo systems are widely adopted due to their high power-to-volume ratio, superior dynamic response performance, and extremely high control accuracy. However, the inevitable presence of nonlinear factors in the system poses a series of challenges for precise mathematical modeling and the design and application of different forms of control strategies. This article aims to explore how various control strategies are specifically implemented to address the nonlinear characteristics of electro-hydraulic servo systems, building upon the research progress in modeling these systems considering nonlinear factors. Subsequently, the article summarizes their innovative applications in electro-hydraulic servo systems. Simultaneously, relevant patents and technologies were reviewed and summarized. The paper provides a detailed comparison and analysis of various nonlinear modeling methods, with a particular focus on the significance of neural networks and fuzzy logic control in enhancing the performance of electro-hydraulic servo systems. The article reveals significant advancements in modern control strategies in dealing with uncertainties and disturbances within the system, offering new perspectives and ideas for improving system efficiency and achieving energy resource conservation with technological progress. The review provides a series of practical recommendations aimed at optimizing the performance of electro-hydraulic servo systems. Despite progress in multiple research endeavors, future research should focus on further enhancing system performance and applying these strategies to a broader range of scenarios.

Thermal dynamic analysis and multi-objective optimization of a 10 kW dual preheating solid oxide fuel cell system

The increasingly serious environmental problems caused by the excessive development of fossil fuels necessitate the promoting of novel and effective energy technologies. As an environmentally friendly and effective promising solution in terms of its low emission, and fuel adaptability, the solid oxide fuel cell (SOFC) system has attracted widespread attention. To better promote the progress of SOFC, the SOFC testing system (SOFC TS) is very important. In this paper, we have established a dual preheating SOFC TS configuration where the fuel is first preheated by exhaust gas, and then preheated by the electric heater to the setting temperature. A comprehensive thermodynamic analysis is conducted to investigate the characteristic of this SOFC TS. Building upon this designed testing system, a multi-objective optimization approach is adopted to enhance the performance of the thermal management subsystem. The results showed that the SOFC stack is the main exergy component in the SOFC TS, the selected point of multi-objective optimization can reduce the thermal management costs by 60$ and improve system efficiency by 4.5%.

Efficient Resource Management and Expansion Scheme for Collaborative Edge-Cloud Computing

Integrating the advantages of both the edge and the cloud, the edge-cloud computing system emerges to provide high-quality computing services for mobile users. To improve system efficiency, we investigate a hybrid mode of resource collaboration and expansion for the edge-cloud computing system, in which edge servers not only can collaborate with the cloud by purchasing high-priority computation resources temporarily but also can expand their local computation resources permanently. In such a way, the edge server can maximize its long-term profit by making a trade-off between the purchasing cost and the expanding cost. By formulating the resource management problem as a long-term profit maximization one, we first analyze the relationships among the expected minimal purchasing cost, the computation delay, and the available computation resources. Then, we design an efficient resource reserving and expanding scheme to determine the optimal expected amounts of reserving resources and expansion resources. Next, we propose an efficient real-time resource purchasing scheme to obtain the optimal amount of real-time purchasing resources dynamically. Finally, simulation results show that the proposed efficient resource collaboration and expanding scheme can maximize the long-term profit while guaranteeing the computation delay.

Smart landscaping design for sustainable net-zero energy smart cities: Modeling energy hub in digital twin

In our study, we introduce an innovative energy management system optimized for energy hubs in net-zero energy smart cities, emphasizing sustainability as a core objective. Our approach intricately integrates distributed generation systems and storage facilities within a digital twin framework, incorporating landscape considerations to promote environmental harmony. By prioritizing sustainability, our strategy aims to minimize operational costs while maximizing energy efficiency and reducing carbon emissions. We employ specialized energy flow algorithms for each grid, designing energy hubs that leverage renewable resources and mobile storage to enhance sustainability. To address complexity, our model utilizes a non-convex mixed-integer nonlinear programming structure and robust adaptive optimization techniques, combining the Gray Wolf and Krill Herd algorithms. Through simulations, we demonstrate significant improvements in power system efficiency, including notable reductions in power loss, peak voltage fluctuations, and temperature variations. Our research underscores the critical role of smart landscaping in advancing sustainable energy management for net-zero energy smart cities, facilitating seamless integration of energy hubs with the surrounding landscape within a digital twin paradigm.

An Efficiency Improvement Strategy for Triple-Active-Bridge-Based DC Energy Routers in DC Microgrids

A triple-active bridge (TAB) can be used as a power conversion unit in a three-port DC energy router (DCER) such as a triple-active bridge-based DC energy router (TAB-DCER). The operational loss of a TAB can be seen as a key factor affecting the efficiency of a TAB-DCER. However, the RMS value of the inductor current of the TAB-DCER increases under single-phase shift (SPS) control, and this greatly increases the system operating losses. The use of phase-shifted plus PWM (PS-PWM) control can reduce the RMS value of the inductor current, but its mathematical model is complex, and involves difficult calculations. To address this problem, in the study reported here, we developed an optimal control strategy for the RMS value of the inductor current based on TAB-DCER. First, the working principle of a TAB-DCER under PS-PWM control was analyzed, and a circuit decomposition model was established. Second, the operating modes under PS-PWM control were analyzed, and corresponding expressions of port power and the RMS value of the inductor current were obtained. Third, an optimized mathematical model of the sum of squares of the RMS value of the inductor current of the TAB-DCER was constructed. Finally, a genetic algorithm was used to solve the mathematical model and derive the optimal phase shift angle; this resulted in a lower RMS value of the inductor current in the TAB-DCER and reduced the system operating losses. The simulation and experimental results show that the TAB-DCER used in the present study can reduce operating losses, improve system efficiency, and deliver coordinated power control.

Multi‐dimensional resource management with deep deterministic policy gradient for digital twin‐enabled Industrial Internet of Things in 6 generation

AbstractIn the era of sixth generation mobile networks (6G), industrial big data is rapidly generated due to the increasing data‐driven applications in the Industrial Internet of Things (IIoT). Effectively processing such data, for example, knowledge learning, on resource‐limited IIoT devices becomes a challenge. To this end, we introduce a cloud‐edge‐end collaboration architecture, in which computing, communication, and storage resources are flexibly coordinated to alleviate the issue of resource constraints. To achieve better performance in hyper‐connected experience, real‐time communication, and sustainable computing, we construct a novel architecture combining digital twin (DT)‐IIoT with edge networks. In addition, considering the energy consumption and delay issues in distributed learning, we propose a deep reinforcement learning‐based method called deep deterministic policy gradient with double actors and double critics (D4PG) to manage the multi‐dimensional resources, that is, CPU cycles, DT models, and communication bandwidths, enhancing the exploration ability and improving the inaccurate value estimation of agents in continuous action spaces. In addition, we introduce a synchronization threshold for distributed learning framework to avoid the synchronization latency caused by stragglers. Extensive experimental results prove that the proposed architecture can efficiently conduct knowledge learning, and the intelligent scheme can also improve system efficiency by managing multi‐dimensional resources.

REVIEW ON LEAKAGE DETECTION MODEL OF WATER DISTRIBUTION SYSTEM FOR NON-REVENUE WATER

Efficient water distribution systems are essential for ensuring global access to clean water, yet the persistent challenge of Non-Revenue Water (NRW) poses a significant threat to the sustainability of water utilities. NRW, comprising losses from leaks, unauthorized consumption, and inaccurate metering, remains a critical concern with economic and environmental implications. The escalating global demand for water highlights the urgency of addressing Non-Revenue Water, with leakage being a substantial contributor to these losses. Leakage models are pivotal tools in understanding and quantifying the factors contributing to water losses. This review consolidates current knowledge on leakage models, offering insights into their applicability in reducing Non-Revenue Water. It aims to guide water engineers, policymakers, and researchers toward effective strategies for minimizing water losses, improving system efficiency, and promoting sustainable water management practices. This paper presents a comprehensive review of leakage models within water distribution systems, focusing on their role in mitigating Non-Revenue Water.

High-speed fluorescence excitation-scanning hyperspectral imaging microscopy using thin-film tunable filters.

Hyperspectral imaging (HSI) technologies have enabled a range of experimental techniques and studies in the fluorescence microscopy field. Unfortunately, a drawback of many HSI microscope platforms is increased acquisition time required to collect images across many spectral bands, as well as signal loss due to the need to filter or disperse emitted fluorescence into many discrete bands. We have previously demonstrated that an alternative approach of scanning the fluorescence excitation spectrum can greatly improve system efficiency by decreasing light losses associated with emission filtering. Our initial system was configured using an array of thin-film tunable filters (TFTFs, VersaChrome, Semrock) mounted in a tiltable filter wheel (VF-5, Sutter) that required ~150-200 ms to switch between wavelengths. Here, we present a new configuration for high-speed switching of TFTFs to allow rapid time-lapse HSI microscopy. A TFTF array was mounted in a custom holder that was attached to a piezoelectric rotation mount (ThorLabs), allowing high-speed rotation. Switching between adjacent filters was achieved using the internal optics of a DG-4 lightsource (Sutter Instrument), including a pair of off-axis parabolic mirrors and galvanometers. Output light was coupled to a liquid lightguide and into an inverted widefield fluorescence microscope (TI-2, Nikon Instruments). Initial tests indicate that the HSI system provides a 15-20 nm bandwidth tunable excitation band and ~10-20 ms wavelength switch time, allowing for high-speed HSI imaging of dynamic cellular events. This work was supported by NIH P01HL066299, R01HL169522, NIH TL1TR003106, and NSF MRI1725937.

Codesign of health technology interventions to support best-practice perioperative care and surgical waitlist management

ObjectivesThis project aimed to determine where health technology can support best-practice perioperative care for patients waiting for surgery.MethodsAn exploratory codesign process used personas and journey mapping in three interprofessional workshops...

Hydrogen production system with near-zero carbon dioxide emissions enabled by complementary utilization of natural gas and electricity

The complementary utilization of different energy sources is a promising strategy for consuming excess electricity and improving system efficiency. In this study, complementary utilization of electricity and natural gas is proposed for a hydrogen production system based on chemical recuperation. The system uses electrolysis technology to convert excess electricity generated from intermittent and fluctuating renewable energy into green hydrogen. It also utilizes the by-product oxygen for oxy-fuel combustion to achieve near-zero carbon dioxide emissions after subsequent compression, transportation, and storage. The system uses natural gas for steam methane reforming to generate hydrogen. A portion of flue gas generated by the combustor is introduced into the reformer, replacing high-temperature steam for reforming with methane. In addition, the waste heat from the flue gas is introduced into the electrolysis cell to save electricity. Energy and exergy analyses of the proposed and reference systems were performed. The results revealed that the energy and exergy efficiencies of the proposed system are 81.20% and 73.29% at near-zero carbon dioxide emission, representing an improvement of 7.09 and 6.41 percentage points, respectively, compared to the reference system. It also appeared that 98.68% in situ oxygen consumption was achieved. The hydrogen mass flow generated by the proposed system is 33.83 kg/h, which is 8.78% higher than the 30.88 kg/h of the reference system. This study introduces a promising method for developing a hydrogen production system with high efficiency and near-zero carbon dioxide emissions.

Transcatheter Aortic Valve Implantation Wait-Time Management: Derivation and Validation of the Canadian TAVI Triage Tool (CAN3T).

Transcatheter aortic valve implantation (TAVI) has seen indication expansion and thus exponential growth in demand over the past decade. In many jurisdictions, the growing demand has outpaced capacity, increasing wait times and preprocedural adverse events. In this study, we derived prediction models that estimate the risk of adverse events on the waitlist and developed a triage tool to identify patients who should be prioritized for TAVI. We included adult patients in Ontario, Canada referred for TAVI and followed up until one of the following events first occurred: death, TAVI procedure, removal from waitlist, or end of the observation period. We used subdistribution hazards models to find significant predictors for each of the following outcomes: (1) all-cause death while on the waitlist; (2) all-cause hospitalization while on the waitlist; (3) receipt of urgent TAVI; and (4) a composite outcome. The median predicted risk at 12 weeks was chosen as a threshold for a maximum acceptable risk while on the waitlist and incorporated in the triage tool to recommend individualized wait times. Of 13 128 patients, 586 died while on the waitlist, and 4343 had at least 1 hospitalization. A total of 6854 TAVIs were completed, of which 1135 were urgent procedures. We were able to create parsimonious models for each outcome that included clinically relevant predictors. The Canadian TAVI Triage Tool (CAN3T) is a triage tool to assist clinicians in the prioritization of patients who should have timely access to TAVI. We anticipate that the CAN3T will be a valuable tool as it may improve equity in access to care, reduce preventable adverse events, and improve system efficiency.

Towards a Regulatory Framework for Electronic Medical Record Interoperability in Canada.

All complex systems are potentially predisposed to failure. Healthcare systems are complex systems that are prone to many errors that can result in dire consequences for patients and healthcare providers. The healthcare system in Canada is under unprecedented strain due to shortages of healthcare providers, provider burnout, inefficient workflows, and a lack of appropriate digital infrastructure. We used failure mode and effects analysis (FMEA) to identify the failure modes for care provided in primary care settings. We identified failure modes in appointment scheduling, patient-provider communications, referrals, laboratory and diagnostic procedures, and medication prescriptions as the main failure modes. To mitigate the detected risks, we recommend solutions to 'close the loop' on failure modes to prevent patients from falling through the cracks, as vulnerable patients who cannot advocate for themselves are most likely to do so. We provide preliminary requirements for a regulatory regime for electronic health records that can reduce provider burnout, improve regulatory compliance, and improve system efficiency, all while improving patient safety, experience, and outcomes.

Optimization Design of Closed-Loop Thermosyphons: Experimentation and Computational Fluid Dynamics Modeling

The well-established practice of integrating heat pipes into thermosyphons is recognized for its efficacy in achieving energy savings. This integration facilitates heat transfer and fluid circulation without requiring additional pumps or energy input, resulting in reduced consumption, lowered operational costs, and an overall improvement in system efficiency. This research explores the energy-saving potential of closed-loop thermosyphons, with a specific focus on their integration in latent heat-based heat pipe technologies in industrial settings. The study systematically investigates the influence of thermosyphon orientation on energy efficiency through a combination of experiments and computational fluid dynamics (CFD) simulations. Thereby, it results in superior heat transfer rates in forced convection scenarios. A closed-loop thermosyphon heat exchanger undergoes evaluation in three panel installation configurations relative to the ground, taking into consideration factors including copper diameters, coolants (with or without R410a), and temperature conditions. CFD validation identifies an efficient thermosyphon design—a panel oriented perpendicularly to the ground and filled with R410a refrigerant at 90 °C. It utilizes a 19.05 mm copper tube for forced convection. This optimized design demonstrates a commendable heat transfer rate of 1485 W and a heat transfer coefficient of 1252 W/(m2·K), significantly enhancing thermal process efficiency and resulting in notable energy savings.

1906 Identifying Older Frail Patients Suitable for Same Day Emergency Care (SDEC); The Applicability of Patient Selection Scoring System

Abstract Aim Several patient selection scores have been developed to identify patients suitable for SDEC from triage in Emergency Departments (ED) and the acute medical intake. Scores are designed to improve system efficiency, overcrowding and patient experience. Studies have been conducted that compare these; none in frail older adults. This study compared the Glasgow Admission Prediction Score (GAPS), Sydney Triage to Admission Risk Tool (START) and the Ambulatory Score (Amb). Methods The Older Person’s Assessment service is ED based, accepting patients with frailty syndromes aged >70 years with same-day discharge for >75% of patients. The OPAS databank was retrospectively analysed from June 2020 to December 2021. Interactions with age, Charlson Co-morbidity index (CCI) and Clinical Frailty Score (CFS) were evaluated alongside each ambulatory score. ED documentation was used to gain triage data. Results 748 attendances, 274(36.6%) Male with mean age 82.8(±8.5) years, CFS 5.2(±1.4) and CCI 6.7(±2.6) with 584(78.1%) discharged same day. Mean Amb score 4.2(±1.7), GAPS 21.4(±5.8), START 23.5(±4.7) all within admission range with 29.1% Mortality within 12 months. There was a significant difference between those admitted and discharged with CFS (p<0.001), mortality (p<0.001), Amb score and START score but not GAPS (p<0.001 vs p=0.03 vs p=0.17). Conclusion Frailty is an important determinant in identifying whether ambulatory care is appropriate. No score could be reliably used as a screen for suitable patients for SDEC services although the Amb score was the most accurate when assessing each individual variable. We are developing our own SDEC score for older, frailer adults which is currently being validated in the OPAS and SDEC settings.