Operational Criteria Research Articles

Improving the Professionalism of Education Personnel in Jambi Province Through Principal’s Supervision Skills

The purpose of this study is to improve school principals’ supervisory skills in order to increase the professionalism of education workers in Jambi Province. A descriptive qualitative technique is used in this descriptive qualitative research. Snowball sampling was used to identify research subjects, which included school principals, vice principals, and educational personnel. Data collection methods include observation, interviews, and documentation. SMAN in Jambi Province is the research location. The study’s findings are the supervisory skills of school principals in increasing the professionalism of education staff in Jambi Province, which include: a) planning through a work program determined by the principal’s policy, b) distributing education staff in their respective tasks, even if some are not according to their expertise, c) in carrying out work such as entering key school data into computers, filing correspondence, distributing correspondence, and storing school goods, and d) administrative work is still rarely supervised at SMA Negeri 1 Jambi City. The study’s conclusion is that administrative professionals must adhere to specified service operational criteria.

Cerebral cortical structural alteration patterns across four major psychiatric disorders in 5549 individuals

According to the operational diagnostic criteria, psychiatric disorders such as schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and autism spectrum disorder (ASD) are classified based on symptoms. While its cluster of symptoms defines each of these psychiatric disorders, there is also an overlap in symptoms between the disorders. We hypothesized that there are also similarities and differences in cortical structural neuroimaging features among these psychiatric disorders. T1-weighted magnetic resonance imaging scans were performed for 5,549 subjects recruited from 14 sites. Effect sizes were determined using a linear regression model within each protocol, and these effect sizes were meta-analyzed. The similarity of the differences in cortical thickness and surface area of each disorder group was calculated using cosine similarity, which was calculated from the effect sizes of each cortical regions. The thinnest cortex was found in SZ, followed by BD and MDD. The cosine similarity values between disorders were 0.943 for SZ and BD, 0.959 for SZ and MDD, and 0.943 for BD and MDD, which indicated that a common pattern of cortical thickness alterations was found among SZ, BD, and MDD. Additionally, a generally smaller cortical surface area was found in SZ and MDD than in BD, and the effect was larger in SZ. The cosine similarity values between disorders were 0.945 for SZ and MDD, 0.867 for SZ and ASD, and 0.811 for MDD and ASD, which indicated a common pattern of cortical surface area alterations among SZ, MDD, and ASD. Patterns of alterations in cortical thickness and surface area were revealed in the four major psychiatric disorders. To our knowledge, this is the first report of a cross-disorder analysis conducted on four major psychiatric disorders. Cross-disorder brain imaging research can help to advance our understanding of the pathogenesis of psychiatric disorders and common symptoms.

A Novel Security Framework to Mitigate and Avoid Unexpected Security Threats in Saudi Arabia

Many organizations around the world suffer large losses due to unexpected risks which can have a profound impact on their survival. This paper presents a novel security framework to address the security needs of Saudi organizations. There are four stages in the security framework: risk assessment and management, security intelligence and analytics, security policies and procedures, and security monitoring. A comprehensive security solution was provided by combining common security frameworks, e.g. ISO/IEC 27001:2013, NIST Cybersecurity Framework, and COBIT. The developed framework was designed to help Saudi organizations identify, assess, and control risks and respond to unexpected events in a timely and effective manner. It is expected to help organizations develop and implement effective security measures to protect their critical assets and operations from security threats. The proposed framework is comprehensive and can cover most organizations' requirements.

A Split-Frequency Filter Network for Hyperspectral Image Classification

The intricate structure of hyperspectral images comprising hundreds of successive spectral bands makes it challenging for conventional approaches to quickly and precisely classify this information. The classification performance of hyperspectral images has substantially improved in the past decade with the emergence of deep-learning-based techniques. Due to convolutional neural networks’(CNNs) excellent feature extraction and modeling, they have become a robust backbone network for hyperspectral image classification. However, CNNs fail to adequately capture the dependency and contextual information of the sequence of spectral properties due to the restrictions inherent in their fundamental network characteristics. We analyzed hyperspectral image classification from a frequency-domain angle to tackle this issue and proposed a split-frequency filter network. It is a simple and effective network architecture that improves the performance of hyperspectral image classification through three critical operations: a split-frequency filter network, a detail-enhancement layer, and a nonlinear unit. Firstly, a split-frequency filtering network captures the interactions between neighboring spectral bands in the frequency domain. The classification performance is then enhanced using a detail-improvement layer with a frequency-domain attention technique. Finally, a nonlinear unit is incorporated into the frequency-domain output layer to expedite training and boost performance. Experiments on various hyperspectral datasets demonstrate that the method outperforms other state-of-art approaches (an overall accuracy(OA) improvement of at least 2%), particularly when the training sample is insufficient.

Using Analytical Hierarchy Process for Double Auction to Optimize Financial Performance of Private Higher Education Institutions

Internal factors and external factors are used to measure the performance of higher education institutions. Internal factors include those whose criteria come from within the organization, while external factors are those whose criteria come from outside the organization. Of these two factors, measurement criteria that can help in decision-making about the development and expansion of higher education competence, including financial criteria, are needed. This study examines the optimization of the financial performance of private higher education institutions by applying the Analytic Hierarchy Process method and a proposed double auction framework. Financial criteria are critical to supporting the development and enhancing the competency of higher education institutions. The Analytical Hierarchy Process is used to prioritize 19 sub-criteria, with the Teaching Process Operational Cost Development sub-criterion scoring highest for each operational criterion. The double auction framework is proposed to facilitate decision-making for the development and further competence of private higher education institutions. This paper represents an important contribution to the evaluation of the financial performance of private higher education institutions by using a novel approach that incorporates a double auction framework.

Enhanced ship cross-section design methodology using peridynamics topology optimization

In this study, peridynamics topology optimization (PD-TO) framework is implemented to reduce the total weight of ship structures and increase their structural endurance against cracks. PD-TO is a general nonlocal optimization strategy that performs the minimization of strain energy density as the objective function and uses pre-defined volume fractions as optimization constraints. To analyze ship structures herein, both the optimality criteria (OC) algorithm and the proportional (PROP) approach are implemented into the PD-TO solver. As the initial design domain, a reference bulkhead geometry of trailing suction hopper dredger (ship) is modeled. This web frame is optimized according to critical wave/loading conditions such as hogging and sagging. Different volume fractions are investigated to obtain lighter designs based on OC and PROP methods. In addition, different cracked scenarios are created by locating the cracks into various positions on the reference ship cross-section. Optimized results for cracked cases shows that the proposed method can create alternative web frames for specific definitions of the possible damaged regions on the board. To prove the efficiency of the proposed method, maximum displacements and compliance of the reference and optimized structures are compared. The results proves that topologically optimized designs offered stiffer structures as compared to conventional designs under the same loading conditions. Finally, some of the optimized results are smoothed to demonstrate the practical utility of the PD-TO for manufacturing. Overall, it is revealed that the PD-TO can be effectively utilized to design marine structures to achieve a higher strength/weight ratio while considering critical operation conditions and possible damaged regions.

Sustainable management in the slow fashion industry: carbon footprint of an Italian brand

PurposeEnvironmental impacts associated with the fashion industry concern society and require commitment to sustainable development goals from leading companies. The role of the luxury sector in setting trends and negotiating power within the supply chain can lead this industry towards sustainability. This study constructs a comprehensive operational flux inventory attributed to an Italian luxury garment brand, aiming to investigate and propose feasible strategies to reduce potential impacts coupled with their products.MethodsUnder the operational control criteria, a whole year of activities was tracked using mainly primary data from its management system. According to ISO 14064–1:2019, potential greenhouse gas emissions were classified, organized, and processed into six categories. The analysis, at the company level, covered the product’s complete life cycle, i.e., from cradle to the grave. The ecoinvent database considered preferentially local geography, and the cut-off system approach, therefore assigning emissions to the primary user.Results and discussionResults showed that the only unit in central Italy where the headquarter is located (excluding retail stores), producing 485,193 women’s clothing in a year, emitted 9804 t CO2 eq. Most of these impacts (69% or 6752 t CO2 eq) can be associated with indirect emissions related to raw products and materials, and about 93% of this amount results from the high-quality products used by the company. Transportation represents 14% of the total emissions, while the use phase accounts for about 13%. As a final step, six different mitigation scenarios were proposed and analyzed by focusing on non-core production activities, i.e., upstream, and downstream operations, and consumers’ habits. Once combined, these strategies can potentially reduce by about 25% the study case company overall emissions.ConclusionsAs a conclusion, exploring possible alternatives through environmental assessment tools can support strategies for achieving impact reduction. While aggressive changes can be done in non-core activities with excellent results, changes perceived by the customers can also be well desired to mark innovation and advances in the business mindset.

NeuroCrossover: An intelligent genetic locus selection scheme for genetic algorithm using reinforcement learning

Researchers have been studying genetic algorithms (GAs) extensively in recent decades and employing them to address extremely challenging combinatorial optimization problems (COPs). Although GAs achieve superior performance, they are less efficient because most GAs are designed manually without intelligent parameter configuration to support scalable problem-solving strategies and learnable evolutionary operators. To address this issue, machine learning (ML) techniques have been integrated with GAs for operator and parameter selection, however, few studies have focused on intelligent genetic locus selection for influential operators in GAs. To fill this gap, this paper proposes an intelligent genetic locus selection algorithm that serves as the foundation of parameter configuration for critical operators. With the established framework, the Cross Information Synergistic Attention (CISA) model and the n-step proximal policy optimization (PPO) have been utilized to intelligently select the appropriate genetic locus for the most influential phase, i.e., crossover, during the evolutionary process. The proposed NeuroCrossover algorithm is validated on extensive COPs, including the traveling salesman problem, capacitated vehicle routing problem, and bin packing problem. The results demonstrate the efficiency and effectiveness of our algorithm, which outperforms other methods in terms of solution quality, convergence speed, and generalization. For instance, with the CISA, the average percentage gaps of our algorithm are 3.64% and 6.38% for instances in TSPLIB and CVRPLIB, respectively, obtaining gains of about 0.47% and 1.20% compared to those of GA. The proposed algorithm provides a novel solution to lead GAs to an efficient search and improve their scalability and learnability.

Implementation of an Online Intraoperative Assessment of Technical Performance for Surgical Trainees

IntroductionAssessment of surgical resident technical performance is an integral component of any surgical training program. Timely assessment delivered in a structured format is a critical step to enhance technical skills, but residents often report that the quality and quantity of timely feedback received is lacking. Moreover, the absence of written feedback with specificity can allow residents to seemingly progress in their operative milestones as a junior resident, but struggle as they progress into their postgraduate year 3 and above. We therefore designed and implemented a web-based intraoperative assessment tool and corresponding summary "dashboard" to facilitate real-time assessment and documentation of technical performance. Materials and methodsA web form was designed leveraging a cloud computing platform and implementing a modified Ottawa Surgical Competency Operating Room Evaluation instrument; this included additional, procedure-specific criteria for select operations. A link to this was provided to residents via email and to all surgical faculty as a Quick Response code. Residents open and complete a portion of the form on a smartphone, then relinquish the device to an attending surgeon who then completes and submits the assessment. The data are then transferred to a secure web-based reporting interface; each resident (together with a faculty advisor) can then access and review all completed assessments. ResultsThe Assessment form was activated in June 2021 and formally introduced to all residents in July 2021, with residents required to complete at least one assessment per month. Residents with less predictable access to operative procedures (night float or Intensive Care Unit) were exempted from the requirement on those months. To date a total of 559 assessments have been completed for operations performed by 56 trainees, supervised by 122 surgical faculty and senior trainees. The mean number of procedures assessed per resident was 10.0 and the mean number per assessor was 4.6. Resident initiation of Intraoperative Assessments has increased since the tool was introduced and scores for technical and nontechnical performance reliably differentiate residents by seniority. ConclusionsThis novel system demonstrates that an online, resident-initiated technical assessment tool is feasible to implement and scale. This model's requirement that the attending enter performance ratings into the trainee's electronic device ensures that feedback is delivered directly to the trainee. Whether this aspect of our assessment ensures more direct and specific (and therefore potentially actionable) feedback is a focus for future study. Our use of commercial cloud computing services should permit cost-effective adoption of similar systems at other training programs.

Assessment of sleep quality and its factors among clinicians working in critical care units and operation theaters at North West Ethiopia, 2022: a multicenter cross-sectional study.

The objective of this study was conducted for the purpose of assessing the quality of sleep and associated factors among clinicians working in the critical care unit and operation theater. A cross-sectional study was conducted from 15 May to 15 June 2022. Data were collected using a self-administered questionnaire from 421 clinicians selected by simple random sampling techniques. Sleep quality was measured by the Pittsburg sleep quality index. The data were entered into Epi-data and exported to SPSS. Frequency and percentage were used for the descriptive analysis. Binary and multivariate logistic regression analysis were used to identify factors associated with poor quality of sleep. The strength of the association was measured with an OR within the 95% CI and P-value of <0.05. About half 220 (52.3%) of the study participants age between 25 and 30 year old and the majority 321 (76.2%) of them were males. The prevalence of poor sleeps quality was 81.5% (95% CI: 77.9-85.5). Working night shift (AOR: 3.37, 95% CI: 1.754-6.484), having depressive symptoms (AOR: 3.25, 95% CI: 1.485-7.147) and having no regular exercises (AOR: 0.299, 95% CI: 0.166-0.537) were predisposing factors for poor sleep quality. The prevalence of poor sleep quality among clinicians working in the ICU and operation room was high. Clinicians who had no regular exercise, who worked in night shift, and who had depressive symptoms were associated with poor quality of sleep. Clinicians should have an awareness on the symptoms of depression, implement sleep hygiene education programs and promoting regular exercise. The authors recommend healthcare policy makers for improving working schedules.

SEAKEEPING EVALUATION OF SHIPS FOR OPERATIONAL PLANNING IN THE GULF OF GUINEA

This paper evaluates the sea-keeping characteristics of a Platform Supply Vessel (PSV) for operational planning in the Gulf of Guinea according to the respective international requirements or standard criteria. The ship’s design and operation characteristics were examined, the characteristics of the specified sea environment in which the ship should perform its mission were assessed, the impact of the specified sea environment on the design and operation of the ship was evaluated and ultimately, the operational criteria that should not be exceeded, so that the ship can perform its mission effectively was determined. Structural Analysis and Design Computer-Aided Design (SACS CAD) Software was employed to model the ship design and it was subjected to the environment in which it is to operate. The Joint North Sea Wave Project (JONSWAP) spectrum was used to model the local wind sea wave with Orca Finite Element Analysis of Flexible Systems (ORCAFLEX). This analysis showed the dynamic movement of the Platform Supply Vessel (PSV) in the various degrees of freedom (heave, surge, sway, yaw, roll, and pitch). Broad-based results showed that the PSV is fit to be operational. This was because of the various tests that were conducted for normal conditions. The various degrees of freedom offset exerted by the PSV were below the tolerance limit of platform supply vessels (10% of water depth of 100m=10m). The results obtained were for the south, the heave offset of 1.6032m and surge offset of 2.1507m. For the southwest, the heave offset of 1.5033m, the surge offset of 1.0712m, and the sway offset of 1.0753m. For the west, the heave offset of 1.068m, and the sway offset of 1.2114m. Local Sea wind wave in the south direction (180°) exerts the most environmental loading on the designed PSV. This was because of the result obtained for the extreme condition (heave offset of 1.9571m and surge offset of 1.4107m. The PSV stability parameters were also obtained as summarized in Appendix C and known to be within the limit of acceptability and validated by comparing the righting lever, GZ, of the designed PSV in Figure 16 with that obtained by marine.info (2021). Both righting levers, GZs were above the 30 degrees requirement of UKMCA (2008) criteria for PSVs. The GZ obtained was 62.8 degrees which should not be exceeded to prevent the PSV from capsizing. The study contributes to the body of knowledge surrounding seakeeping evaluations of PSVs and serves as a foundation for evaluating the design and performance of these vessels in the demanding offshore environment

Human Performance in Highly Automated, Cyber Vulnerable Unmanned Aerial Systems: Effects of Operators’ Background and Task Load

This article evaluated the effects of operator background and task load on operator ability to detect and respond to cyber events while controlling multiple unmanned aerial systems (UAS). Cyber physical systems (CPS) are susceptible to cyber threats and associated events via connections critical to their operations. The effects of cyber intrusions on UAS operator performance as a function of background and task load have been understudied. Fifty-one operators with different backgrounds (Aviators, Gamers and Non-Gamers; n = 17 per group) were evaluated across two levels of task load (in-the-loop (ITL) and out-of-the-loop (OTL)) while controlling a simulation of multiple UAS involving cyber events. Cyber events represented spoofed information that could not be corroborated with available secondary information/displays. Multivariate analysis of variance was used to analyze the effect of background and task load on operator performance, subjective perception of workload (assessed using the NASA Task Load Index), and trust. Nongamers responded to cyber events 62.8% and 67.7% slower than aviators and gamers, respectively. Mean response times across task load conditions were substantially longer for cyber events (128.9 s) than for noncyber, “real” events (42.8 s). Scenario type (ITL/OTL) was statistically significant for workload, cyber classification, and cyber action response. The findings may inform recruitment criteria for future UAS operators. Individuals with gaming experience may be as adept at responding to cyber events while operating multiple UAS as aviators. Cyber events are likely to affect the performance of the overall CPS due to their impact on the human operator.

Numerical studies on tugboat performance during pushing operations

This paper introduces a RANS CFD methodology for the evaluation of tugboat dynamics during pushing operations. Two- and three- dimensional methods that respectively utilize “Dynamic Fluid Body Interactions - (DFBI)” and “Tug Force Equilibrium kinematics-(TFE)” are assessed and compared with the aim to better understand the influence of fluid modelling on ship dynamics. For the DFBI method, an unsteady RANS solver comprising of a dynamic fluid body interaction module and a contact mechanics coupling algorithm are used to predict the forces between a tugboat and an assisted ship. For the TFE method, a steady RANS method is applied and contact actions are calculated as a sum of the hydrodynamic forces on the hull and the propeller. Whereas DFBI accounts for the time variation of the contact forces, the TFE is more rapid and could be used to derive operational decision support criteria. To demonstrate the latter the TFE method is used to derive the pushing forces based on a set of 16 numerical simulations. It is concluded that irrespective of the model used the tugboat speed and orientation may amplify the pushing forces. This effect could be prominent, especially at slow speeds for which the sway force acts in opposite direction to the tug.

Clients as drivers of innovation in the infrastructure sector: implications of hard and soft project management approaches

PurposeBy adopting the “hard” and “soft” project management (PM) approaches from the PM-literature, this paper aims to problematize the expected role of client organizations in driving innovation in the transport infrastructure sector.Design/methodology/approachAddressing a large public client in Sweden, a case study design was initially applied to provide in-depth insights and perspectives of client project managers’ views and experiences of managing projects expected to drive innovation. In this paper, the concepts of “hard” and “soft” are used to discuss empirical findings on challenges associated with adopting a PM-approach for driving innovation in projects. The empirical material consists of interview data, complemented with observations and archival data.FindingsFindings reveal challenges associated with combining hard and soft approaches, frequently demonstrating difficulties in balancing short-term project expectations with the promotion of innovation. In line with the literature, project managers note that there is a need for soft approaches to promote development and drive innovation. Yet, findings reflect a situation in which operational success criteria predominate, whereas soft approaches are not sufficiently used to create the grounds required for fostering innovation.Originality/valueInsights are provided into how PM-approaches may impact construction innovation in the infrastructure sector, demonstrating a need for further research on the challenges and implications of applying and combining hard and soft PM-approaches.

An Experimental and Computational Approach to Development of Mixing Processes for Miscible Liquids in Unbaffled Tanks.

Mixing of liquids is a critical unit operation in the biopharmaceutical drug product manufacturing. It commonly consists of mixing miscible liquids to dilute bulk drug substance (DS) or pool multiple lots of drug substance. In the past, at-scale mixing studies have been conducted to determine the mixing parameters, namely mixing speed, and mixing time. At-scale studies have historically been utilized to overcome the challenges associated with geometric dissimilarity of mixing systems found when scaling up. In addition, such studies are quite costly, as they often use actual DS to overcome a lack of representativeness associated with simple salt trace models often employed. As a result, there is a significant need for alternative cost-effective methods that can predict mixing parameters with close agreement to actual experiments and operations. At-scale mixing experiments were conducted using full-sized tanks and surrogate solutions. Several computational fluid dynamic (CFD) simulation methods were conducted and compared with the experiments to determine the most reliable computational techniques. The experiments demonstrate that surrogate solutions can be used reliably to determine mixing parameters in at-scale studies instead of the valuable drug products. Studying different CFD methods also showed that transient simulations that use a large eddy simulation (LES) viscous modeland a sliding mesh can correctly predict the mixing parameters. Results of this study establish a practical and reliable methodology to perform mixing studies for miscible liquids with different kinematic viscosities. The methods discussed herein greatly reduce the routine mixing study costs in the biopharmaceutical industry and increase efficiency and accuracy of the results, allowing proactive scale-up of mixing operations.

Thermal Runaway Behaviors and Kinetics of NCM Lithium-Ion Batteries at Different Heat Dissipation Conditions

The lithium-ion battery (LIB) thermal runaway is triggered by the exothermic reactions between electrode materials and other active substances such as electrolytes. In this study, the effects of ambient temperature and heat transfer coefficient on the thermal responses and chemical kinetic features of LiNi1/3Co1/3/Mn1/3O2/graphite battery thermal runaway at high-temperature abuse conditions are investigated using a validated 2D axisymmetric model. With varied heat transfer coefficients of the LIB, the corresponding runaway, critical, and safety operation zones at different ambient temperatures are quantitatively distinguished. The results reveal that, with increased heat transfer coefficient, the critical ambient temperature, T c, triggering thermal runaway increases. However, T c almost remains 430 K when the heat transfer coefficient is higher than 25 W/(m2K). Additionally, based on the thermal response of LIB, the ambient heat absorption stage, ambient heat dissipation stage, and dramatic heat release stage in thermal runaway are defined. It is found that a higher heat transfer coefficient efficiently causes a shorter ambient heat absorption stage, which is the primary reason for the reduced delay time for the thermal runaway. Further, kinetic analysis is conducted at different heat exchange conditions, and the correlation between LIB thermal responses and the heat release of side reactions in different operation zones is clarified. Specifically, the reactions between the electrolyte and negative/positive electrodes are the most exothermic and most influential of all side reactions, and their influence on the maximum temperatures and runaway delay times is promoted with an elevated heat transfer coefficient.

Dynamics of Current-Sharing Within a REBCO Tape-Stack Cable

Current redistribution in a non-insulating REBCO tape-stack cable may enable the use of such a cable in a high field dipole without provision for transposition of the constituent tapes. As current is increased in the REBCO cable a dynamic resistance arises in the superconducting layer near operation at critical current. The critical current of each tape in the stack is determined by the local magnetic field variation within the cable. The superconducting-normal transition in REBCO occurs over a working range of current and, within that range, the longitudinal Ohmic electric field produces a transverse electric field between adjacent tapes with different critical currents. Circuit models indicate that, as a given tape approaches critical operation, current will naturally redistribute to neighboring tapes with higher current carrying capacity due to the dynamic rise in resistivity thus preventing premature quench. A multi-scale model is being developed to study the dynamics of current-sharing, the limits of stability, and the impact of fluctuations in critical-current density along each tape.

Techniques of Fluidic Thrust Vectoring in Jet Engine Nozzles: A Review

Thrust vectoring innovations are demonstrated ideas that improve the projection of aerospace power with enhanced maneuverability, control effectiveness, survivability, performance, and stealth. Thrust vector control systems following a variety of concepts have been considered for modern aircraft and missiles to enhance their military performance. Short Take-off and Landing (STOL) and control effectiveness at lower aircraft speeds can be achieved by employing Fluidic Thrust Vectoring Control (FTVC). This paper summarizes a range of ideas for FTVC that have been designed and tested both computationally and experimentally to determine the thrust vectoring performance of supersonic propulsion system nozzles. The conventional method of thrust vectoring involves mechanical means to deflect the direction of flow of the exhaust gases, whereas the most recent method involves fluidic-based thrust vectoring techniques. Fluid-based thrust vectoring has the advantages of simplicity and low weight over mechanical-based thrust vectoring, which has complex geometry and adds extra weight to the aircraft. The fluidic vectoring control nozzles are divided into seven categories: shock vector, bypass shock vector, counterflow, co-flow, throat skewing, dual throat, and bypass dual throat nozzle control. This paper provides a summary of each fluidic thrust vectoring technique with its characteristics, design, classification, and different operational criteria developed to date and compares the intrinsic characteristics of each technique. Based on the present literature, it is concluded that among all the fluidic control techniques, the bypass dual-throat nozzle control can achieve better thrust vectoring performance with large vector angles and low thrust loss.

Evaluation of Multi-Utility Models with Municipal Solid Waste Combustion as the Primary Source under Specific Geographical and Operating Conditions

Developments in waste incineration technology in terms of efficient fuel preparation, combustion, and emissions reduction, as well as the growing needs of the community in terms of electricity, water, and air conditioning loads, are the prime motive for this study. This study presents a novel approach, in which three models of the fluidized bed combustion of municipal waste for simultaneous power generation, freshwater production, and district cooling are analyzed for their energy and exergy performance. The three simultaneously evaluated utility models are different configurations of a fluidized bed combustion system with Rankine cycle power generation, cooling with a vapor absorption refrigeration system, and fresh water production using multiple effect desalination. The output from the turbine, cooling system, and desalination system is determined using the Engineering Equations Solver for different boiler operating pressures. Energy and exergy analysis data for different pressures are used to identify the best configuration. Two variants of the absorption cooling system, namely, single effect and double effect, are considered. The variants of the multiple-effect desalination are the three-stage and five-stage methods. Input parameters used in this study are municipal solid waste generation and composition data collected for an urban community in an arid climate zone with high demand for electric power, cooling, and fresh water. Model 2, which contains two turbines with the reheating and cooling systems connected to a high-pressure turbine and water desalination connected to a low-pressure turbine, gave the best overall performance. Significant savings in terms of the replacement of conventional energy were observed from these waste conversion plants with greater benefits in arid weather conditions. The results obtained by different models under different operating criteria constitute a guideline for municipal planners for the selection of appropriate waste utilization technology, as well as the appropriate operations.

From blackouts to breakthroughs: Examining electricity's relevance in healthcare during COVID-19 and the future role of renewable energy

Power supply played a critical role during the COVID-19 pandemic in keeping hospitals and critical medical equipment operating, which was quickly reflected in electricity consumption and new consumption patterns. However, not all countries faced the same challenges. While developed countries could react adequately to changes in hospital electricity consumption patterns, low-income countries faced infrastructure and energy access challenges during the pandemic, which hampered the management of the pandemic in all of its dimensions. This paper reviews the importance of power supply in hospitals through a literature review and divides the discussion into three sections. First, the factors influencing new hospital consumption patterns during the pandemic are discussed. Then, the consequences of the lack of electricity in remote areas on managing the pandemic are reviewed. Finally, the impact of the pandemic on the design of hybrid power generation systems is reviewed, which must not only provide autonomy for similar future scenarios but also be prepared to respond to sudden increases in power consumption due to a greater number of patients or longer working hours, an increase in the number of critical loads, and possible restrictions on access to fuel. Thus, this work provides valuable insights for policymakers, academics, and researchers on the importance of updating hospital power supply standards and contributes to demonstrating the need to electrify remote hospitals.