Operational Perspective Research Articles

Article: Reflections on the New Rules of Origin of Mercosur*

This article analyses to what extent the new Mercosur’s Rules of Origin contribute to facilitating trade from the perspective of commercial operators. It reflects on whether this compilation and updates help simplify the tasks of commercial operators. For this purpose, specific characteristics of some chapters of the New Rules of Origin (NRO) will be addressed, briefly detailing their structure and analysing the wording and impact of certain articles considered crucial for an operator to declare a product as originating

Fair Energy Trading in Blockchain-Inspired Smart Grid: Technological Barriers and Future Trends in the Age of Electric Vehicles

The global electricity demand from electric vehicles (EVs) increased by 3631% over the last decade, from 2600 gigawatt hours (GWh) in 2013 to 97,000 GWh in 2023. The global electricity demand from EVs will rise to 710,000 GWh by 2030. These EVs will depend on smart grids (SGs) for their charging requirements. Like EVs, SGs are a booming market. In 2021, SG technologies were valued at USD 43.1 billion and are projected to reach USD 103.4 billion by 2026. As EVs become more prevalent, they introduce additional complexity to the SG landscape, with EVs not only consuming energy, but also potentially supplying it back to the grid through vehicle-to-grid (V2G) technologies. The entry of numerous independent sellers and buyers, including EV owners, into the market will lead to intense competition, resulting in rapid fluctuations in electricity prices and constant energy transactions to maximize profit for both buyers and sellers. Blockchain technology will play a crucial role in securing data publishing and transactions in this evolving scenario, ensuring transparent and efficient interactions between EVs and the grid. This survey paper explores key research challenges from an engineering design perspective of SG operation, such as the potential for voltage instability due to the integration of numerous EVs and distributed microgrids with fluctuating generation capacities and load demands. This paper also delves into the need for a synergistic balance to optimize the energy supply and demand equation. Additionally, it discusses policies and incentives that may be enforced by national electricity carriers to maintain grid reliability and manage the influx of EVs. Furthermore, this paper addresses emerging issues of SG technology providing primary charging infrastructure for EVs, such as incentivizing green energy, the technical difficulties in integrating diverse hetero-microgrids based on HVAC and HVDC technologies, challenges related to the speed of energy transaction processing during fluctuating prices, and vulnerabilities concerning cyber-attacks on blockchain-based SG architectures. Finally, future trends are discussed, including the impact of increased EV penetration on SGs, advancements in V2G technologies, load-shaping techniques, dynamic pricing mechanisms, and AI-based stability enhancement measures in the context of widespread SG adoption.

Modeling and Estimating the Effect of a Mix of Varying Levels of Automated Vehicles on Operational Performance of Urban Freeways

Automated vehicles (AVs) will likely influence various aspects of the existing transportation system in the next few decades. Existing literature documents the operational benefits of AVs at different penetration rates. However, estimating the effect of the mix of different levels of AVs on the operational performance of traffic flow has not been explored in the past. This study employs a microsimulation approach to model and estimate the potential effect of varying levels of AVs on the operational performance of freeways. The proposed approach involves a two-step process for calibrating the simulation model. In the first step, the model is calibrated from an operational perspective. In the second step, the calibration is performed from a safety perspective. Thirteen scenarios were generated considering varying penetration rates of different levels of AVs. Congestion index (CI), buffer time (BT), travel time uncertainty (TTU), and delay were computed for each scenario and segment type. The estimations indicate that increasing the penetration of level 3 to level 5 AVs significantly reduces CI, BT, TTU, and delay. In contrast, the effect of level 1 and 2 AVs on freeway operational performance is negligible. Notably, the operational benefits are more pronounced with higher penetration of level 3 and higher AVs. Additionally, the reduction in delay is greater on interchange segments compared with basic freeway segments. The study findings are valuable insights concerning the operational performance of freeways under varying penetration of different levels of AVs, assisting practitioners in formulating AVs-inclusive policies.

Proposals on Effective Implementation of the Carbon Intensity Indication of Ships

The Carbon Intensity Indicator (CII) regulation is a short-term measure of IMO for reducing GHG emissions from ships. In addition, the 2023 IMO GHG Strategy describes that the CII regulation is anticipated to create a potential synergy effect with other measures. Accordingly, the CII regulation, which took effect in 2023, is forecast to increasingly impact international shipping and the commercial vessel market. However, efforts to improve energy efficiency and implement slow steaming for ships are insufficient to meet the CII regulation that is increasingly stringent over time. Therefore, there is a growing need for fundamental improvements in future response strategies. In this study, major causes of low CII ratings for ships were investigated from a recent consulting project that was conducted to support shipping companies in satisfying the regulation from operational and technical perspectives. Lastly, proposals to implement the CII regulation effectively and to reduce GHG emissions from ships fundamentally were made, taking into account the major causes derived from the consulting.

Triboelectric signal enhancement via interface structural design and integrated with deep learning for real-time online material recognition

Triboelectric nanogenerator (TENG) is a promising technology for material recognition due to a large amount of distinguishable feature information in triboelectric signal when the TENG device touches different materials. Nevertheless, the identification precision has only improved from the perspective of sensor construction and operation of design, rather than from the electrodes and the triboelectric interface structure. To prevent such issues, a design strategy of electrode/triboelectric material interface structure is applied to enhance the output performance and recognition accuracy. Electroless nickel was plated on a sponge to fabricate a TENG device electrode with a roughness of 179.1 µm. A coarse triboelectric material/electrode interface can improve the output performance of corresponding device. Hence, the nickel layer surface generates more the triboelectric charges, further leading to characteristic triboelectric signals, which can be distinguished by deep machine learning. As expected, the collected TENG signal has the unique characteristic of being able to identify the touched material with a recognition accuracy of 96 %. Based on this, combined with deep machine learning and the triboelectric effect, a material awareness system integrating TENG-based sensors, data collation, and display components was also designed and built for real-time material type identification with superior accuracy. The potential application advantages of the manufactured TENG device in nonvisual intelligent recognition can be foreseen.

An exploration of community food pantries in Scotland: strategic and operational perspectives on addressing food insecurity and health inequalities

Introduction: Food insecurity and health are inextricably linked. Since 2008, Scotland has witnessed a proliferation of both food insecurity and emergency food provision. There is a recognised commitment from Scottish Government to ‘end the need for food banks’, however, the food aid landscape was ‘turbo-charged’ during COVID-19 leading to intense expansion and diversification of food-based projects, including the development of community food pantries (CFPs). These ‘new’ models are relatively under-researched, meaning we do not adequately understand their potential or realised impacts on food insecurity and health. This study aims to fill that gap.MethodsA qualitative methodology was used to collect and analyse data from in-depth interviews with 10 representatives from both operational and policy settings related to food insecurity in Scotland. In addition, we conducted an analysis of policy documentation from Scottish Government related to tackling food insecurity to understand how CFPs fit into its overall strategy to transition away from food bank use.ResultsWe found there were variations in conceptualisations of CFPs and how they operate, challenges related to addressing food insecurity at a community level and varied narratives around the role of community level interventions in tackling health inequalities. Choice and access to services were viewed as central components to the pantry model. However, there were significant challenges faced by CFPs, including territorialism, funding and food supply. Articulations of health were often multi-layered and complicated with strong recognition of the social determinants as well as acknowledgement of the limitations of tackling food insecurity and health inequalities solely at the community level.ConclusionsDespite a commitment to transition away from emergency food provision, CFPs in Scotland appear to face many of the same issues as food banks, particularly those which impact health. Urgent critique of their reliance on surplus food redistribution is required alongside investigation of how these ‘new’ models are experienced by the people who access them. Further expansion of these models should be viewed with caution and in the same vein as traditional emergency food provision: a symptom of, rather than a solution to, the problem of food insecurity.

Optimization of a Typical Gas Injection Pressurization Process in Underground Gas Storage

In the early construction of an underground gas storage facility in an oil and gas field in southwest China, the increasing gas injection volume led to a continuous rise in energy consumption, which affects the economic sustainability of gas injection and extraction. In order to improve efficiency and reduce energy consumption, optimization of the pressurization process was carried out. An optimization model for the process of pressurization in underground gas storage has been established. Based on the model, a joint optimization approach is applied, where MATLAB is responsible for the iterative process of finding the optimal parameter combinations and HYSYS is responsible for the establishment of the process and calculation of the results of the process parameters. The key parameters include the outlet parameters of the compressor and the air cooler, which are critical in determining the overall energy consumption and operational performance of the system. Accordingly, the results related to the optimal parameter combinations for two-stage compression and three-stage compression were obtained in the case study. Compared with one-stage compression, two-stage and three-stage compression can diminish energy consumption by 1,464,789 kJ/h and 2,177,319 kJ/h, respectively. The reduced rate of energy consumption of three-stage compression was 16.10%, which was higher than that of two-stage compression by 10.83%. Although the construction costs of three-stage compression were higher than those of two-stage compression, from the perspective of long-term operation, three-stage compression had lower operating costs and superior economy and applicable value. The research results provided scientific references and new ideas for the optimization and adjustment of the pressurization process in underground gas storage.

A game-based power system planning approach considering real options and coordination of all types of participants

With the ongoing advancement of global power marketization, the increasing diversity of stakeholders in the power market and their interactions have a significant impact on power system planning and operation. Traditional methods employ game theory to describe the interactions among market participants. However, these approaches fail to include all relevant participant types and overlook the long-term uncertainty value of planning schemes. Therefore, this paper proposes a game theory-based power system planning approach considering real options (RO) and coordination of all types of participants. First, the dynamic gaming interaction among supply-transmission-demand is studied, and the independent system operator is integrated into the game planning framework based on the overall perspective of power market operation. Moreover, the new power supply, grid planning, and operation of distributed generation (DG) are taken as decision variables based on the RO theory, and a game decision model of all participants in the power system planning considering the investment uncertainty is constructed. Finally, the iterative search algorithm is employed to solve the model, and the framework is validated based on the IEEE 30-bus system. The results indicate that through collaborative planning involving various market participants, Generation Companies and Transmission Companies expand their investments to maximize profits, while large power consumers reduce their investment in DG and instead increase their direct power purchases to lower costs. Moreover, these participants are inclined to pursue projects with higher asset value volatility, which further enhances their profit. By integrating RO theory with game theory, the proposed approach establishes a comprehensive planning framework that effectively addresses investment uncertainty. This integration enables market participants to make more optimal decisions, ultimately leading to an enhancement in the long-term economic performance of the power system.

Navigating the Complexity: The Sustainability Challenges in Global Value Chains

The global value chain (GVC) framework may provide a systematic approach to depict and advance sustainable path options at the global, national, and local scales. However, a coherent picture of the fragmented body of knowledge on the sustainability implications of GVCs is lacking. In an attempt to delineate the most effective perspective for addressing sustainability challenges within GVCs, this review explores the main academic streams that have emerged in response to the pressing need for detailed insights into GVCs. These academic streams include sociological, economic, and management approaches. We examine the intersections and distinctions among them, evaluating whether they converge or diverge in addressing sustainability within GVCs. By discussing the limitations and potential of these approaches, we suggest a possible integrated and appropriate research agenda to achieve an encompassing and still operative perspective to address current sustainability challenges.

Quantitative evaluation and optimization of synergistic regulation performance considering wear in short-term response of hybrid pumped storage systems

Amid the extensive integration of renewable energy sources and rapid development of variable-speed pumped storage systems (VPSSs), demanding regulation tasks introduce risks to hydraulic-mechanical systems, revealing a growing trade-off between wear and regulation. From the economic and safe operation perspective, this paper aims to accurately quantify and enhance comprehensive regulation performance of hybrid pumped hydro storage systems (HPHSSs) with VPSS. First, a generic framework is established to quantitatively evaluate synergistic regulation performance (SRP), combining regulation intensity and frequency suppression effect of each unit type. Next, a frequency-division coordinated control method is proposed based on the amplitude-frequency characteristics, designed to leverage the rapid response capabilities of VPSS, and the coupling mechanism between this method and the conventional speed limiter module in affecting system dynamics is elucidated. Finally, comprehensive evaluations of HPHSS under typical disturbance scenarios are conducted, with frequency-division parameter further optimized for different system configurations. The results indicate that HPHSS exhibits excellent global stability with the coordinated control, reducing magnitude of average frequency deviation from 10−3 to 10−4, greatly enhancing the SRP. Additionally, an optimal cut-off frequency is identified within 0.05–0.5 Hz, showing an increasing trend as VPSS proportion decreases. These findings provide a novel sight for the safe and optimized operation of HPHSS.

Analysis of the exergy transfers in subcritical and transcritical CO[formula omitted] ejectors and their connection with the performance of the refrigeration cycle

Ejector refrigeration systems (ERSs) operating with carbon dioxide are notoriously challenging from both design and operation perspectives. In particular, the ejector itself gives rise to special attention since it directly affects the performance of the global system. In this study, the connections between local exergy transfers within the ejector and global cycle performance are investigated by using a novel multi-scale numerical approach. Computational Fluid Dynamics (CFD) is used to generate accurate predictions of the ejector operation with access to the local flow and heat transfer features. The exergy tube analysis is applied onto the simulation results, linking local transfers within the ejector to the results at the component- and cycle-scale. A state-of-the-art ejector thermodynamic model is then calibrated onto the CFD results, and employed to determine the physically possible operation of the ERS. In addition, the metastability impact on the exergy transfers and overall system performance is investigated by comparing the CFD results of the classical Homogeneous Equilibrium Model with those obtained with the Homogeneous Relaxation Model. Notably, it is found that at fixed ejector inlet conditions, there exits an outlet pressure that maximizes the exergy transfers from primary to secondary streams. Interestingly, this work shows for the first time that the maximum exergy gain of the secondary stream appears to correlate with the maximum coefficient of performance of the system, independently of the on- or off-design operation of the ejector. Moreover, metastability generally deteriorates the performance at both scales. The results of the present study serve to pave the way towards better ejector design objectives.

Regularisation and central limit theorems for an inverse problem in network sampling applications

ABSTRACT An inverse problem motivated by packet sampling in communication networks and edge sampling in directed complex networks is studied through the operator perspective. The problem is shown to be ill-posed, with the resulting naive estimator potentially having very heavy tails, satisfying non-Gaussian central limit theorem and showing poor statistical performance. Regularisation of the problem leads to the Gaussian central limit theorem and superior performance of the regularised estimator, as a result of desirable properties of underlying operators. The limiting variance and convergence rates of the regularised estimator are also investigated. The results are illustrated on synthetic and real data from communication and complex networks.

Assessment of earthquake location uncertainties for the design of local seismic networks

The ability to estimate earthquake source locations, along with the appraisal of relevant uncertainties, is paramount in monitoring both natural and human-induced micro-seismicity. For this purpose, a monitoring network must be designed to minimize the location errors introduced by geometrically unbalanced networks. In this study, we first review different sources of errors relevant to the localization of seismic events, how they propagate through localization algorithms, and their impact on outcomes. We then propose a quantitative method, based on a Monte Carlo approach, to estimate the uncertainty in earthquake locations that is suited to the design, optimization, and assessment of the performance of a local seismic monitoring network. To illustrate the performance of the proposed approach, we analyzed the distribution of the localization uncertainties and their related dispersion for a highly dense grid of theoretical hypocenters in both the horizontal and vertical directions using an actual monitoring network layout. The results expand, quantitatively, the qualitative indications derived from purely geometrical parameters (azimuthal gap (AG)) and classical detectability maps. The proposed method enables the systematic design, optimization, and evaluation of local seismic monitoring networks, enhancing monitoring accuracy in areas proximal to hydrocarbon production, geothermal fields, underground natural gas storage, and other subsurface activities. This approach aids in the accurate estimation of earthquake source locations and their associated uncertainties, which are crucial for assessing and mitigating seismic risks, thereby enabling the implementation of proactive measures to minimize potential hazards. From an operational perspective, reliably estimating location accuracy is crucial for evaluating the position of seismogenic sources and assessing possible links between well activities and the onset of seismicity.

Dentistry and Covid-19 in Ghana: operational and economic perspective

Dentistry and Covid-19 in Ghana: operational and economic perspective

A Study on Designing Cyber Training and Cyber Range to Effectively Respond to Cyber Threats

As cyberattacks become increasingly sophisticated with advancements in information and communication technology, the impact of cyberspace threats is growing in both civilian and defense sectors. The utilization of cyber capabilities in operations is on the rise, prompting major nations to continuously enhance their cyber capabilities. This study aims to establish a systematic approach to cyber operations training and propose a framework for the development of cyber training. A hybrid cyber training system is designed as a plan for temporal and spatial integration to simultaneously combine simulation-based training with real-world target training. To develop this concept, a literature review was conducted, expert consultations were held, and data were collected and analyzed through visits to relevant organizations and units. Additionally, the fundamental components of cyber training were examined from environmental, scenario-based, and operational perspectives, leading to the presentation of a development direction for effective cyber training. This study is anticipated to enhance response capabilities to evolving cyber threats and attacks, improve cyber operational proficiency, and secure cyber power to achieve dominance in cyberspace.

Beyond The Wi-Fi Era

The continual progress pace of the development of the Wi-Fi generations may not fulfill the expected tremendous data growth of future smart-home network devices and applications. Throughout this article, we show a comprehensive design of the futuristic smart-home network that distributes massive data for indoor devices while fully supporting intelligent functions. We start by drawing a vision for various application scenarios of information and communication technologies in smart-home networks beyond the 2030s. Then, we appraise the technical specifications of the candidate intelligent home network. To achieve these technological speculations, we propose a novel holistic networking solution that is efficient and intelligent from service and operation perspectives. Specifically, we detail the proposed network architecture, elements, and enabling technologies. To accelerate the research progress and implementation, we further point out the future research directions. Finally, we discuss the non-technological factors that could affect the future deployment of the proposed network solution.

Moderate to severe anemia at admission increases the risk of complications in patients over 60 years with hip fracture

BackgroundAnemia frequently occurs in patients with hip fractures and represents a risk factor that can potentially be altered. To evaluate the association between admission anemia and complications in older hip fracture patients while exploring the potential impact of anemia on complications from the perspective of overall, operation and non-operation.MethodsThis retrospective study enrolled in-patients over 60 years old with hip fractures from January 2020 to November 2023. At admission, anemic patients were identified as having a hemoglobin level below 12 g/dL in females and 13 g/dL in males. Anemia was further classified as mild, moderate, or severe. Data encompassing demographics, comorbidities, medications, information on fracture and surgery, and complications were collected.ResultsA total of 462/679 patients had anemia, including 348, 105, and 9 with mild, moderate, and severe anemia, respectively. A total of 281 individuals experienced complications, including 212 and 69 with and without operation, respectively. Multivariate regression analysis identified anemia as a greater risk for acute heart failure (OR = 2.056, p = 0.037, 95% CI 1.043–4.052) than non-anemia. Moderate to severe anemia was a significant risk factor for any complication (OR = 1.584, p = 0.028, 95% CI 1.050–2.390), ≥ 2 (OR = 2.364, p = 0.001, 95% CI 1.443–3.872) or 3 (OR = 2.311, p = 0.022, 95% CI 1.131–4.720) complications, delirium (OR = 2.301, p = 0.018, 95% CI 1.156–4.579), venous thromboembolism (OR = 2.031, p = 0.042, 95% CI 1.025–4.025), and acute heart failure (OR = 2.095, p = 0.016, 95% CI 1.145–3.834), compared with mild to non-anemia. Similar results were observed in operated patients, while anemia and its severity were not associated with complications in non-operated patients.ConclusionModerate to severe anemia caused complications in elderly hip fracture patients, but it was not observed in non-operated individuals. These findings would support orthopedic physicians’ hierarchical management of anemic patients.

Assessing operational resilience in food supply chains: a discrete-event simulation approach based on a framework for integrated decision-making

ABSTRACT Food supply chains (FSCs) play a critical role in ensuring food security but face increasing vulnerabilities to disruptions. With the objective to mitigate these challenges, this study focuses on assessing operational resilience within the Austrian dairy supply chain during sudden demand spikes. For this purpose, we introduce a novel framework for integrated decision-making which encompasses strategic, tactical, and operational perspectives, augmented with modular building blocks for FSC modelling and simulation. Based on this framework, we develop a discrete-event simulation model to assess and quantify the impact of strategic, tactical, and operational interventions on operational resilience. Our analysis reveals the effectiveness of upstream buffer stocks, adapted reordering strategies, and operational adjustments in response to demand increases. However, no single intervention consistently outperforms others across all performance metrics, emphasising the importance of tailored intervention selection. Hence, the major contributions, i.e. (1) the framework for integrated decision-making and (2) the quantification of potential interventions to enhance operational resilience, are useful for improving the operational resilience of FSCs and increase their ability to supply essentials in the short term despite disruptions. The results assist FSC actors in making more informed decisions to enhance operational resilience.

Research on Production Operation System of Sucker Rod Pumping Units

Oil is the most important raw material in modern industry, and its extraction mainly relies on natural flow and artificial lifting. Sucker rod pumping is currently the most widely used method of artificial lifting for mechanical oil extraction, accounting for about 60% to 70% of all methods. This paper deeply explores the theoretical methods involved in the production operation process of sucker rod pumping units. From the perspective of sucker rod pumping unit production operation, a literature review is conducted on the flow patterns in the wellbore, pump efficiency analysis, and intermittent oil extraction systems, clarifying the optimization objectives of liquid production and system efficiency, and sorting out from the aspects of dynamic liquid level, pump efficiency, reasonable submergence depth, and intermittent operation systems. Through in-depth analysis of these key areas, a solid methodological foundation is provided for the future design and development of sucker rod pumping unit production operation systems.

Physical Fitness Determinants of a Military Casualty Evacuation Test.

Casualty evacuation has been identified as a typical and essential single military task which every soldier should be able to perform rapidly during combat. Previous studies suggest that casualty evacuation is typically conducted by dragging and demands e.g., lean body mass and anaerobic performance. Association of physical fitness with casualty evacuation by dragging has been studied widely but previous studies lack comprehensive assessment of all physical fitness determinants. The purpose of the present study was to examine comprehensively how casualty emergency evacuation (CEE) performance associates with physical fitness and body composition. A total of 25 conscripts (20 men, 5 women) volunteered for measurements of height, weight, waist circumference, body composition, 1-min sit-ups and push-ups, grip strength, isometric bench and leg press, standing long jump, 30-s cycle ergometer test, and 12-min run test. Subjects performed a CEE test in which evacuation time (ET), heart rate, blood lactate concentration, and rate of perceived exertion were measured. In the CEE test, subjects wore combat gear (11.7 ± 1.6 kg) and dragged a doll wearing combat gear (80.2 kg) 28 m while crawling (go round two cones, Z-pattern) and 20 m upright (straightforward). Correlations and backward regression analysis were used for statistical analyses. The level of significance was set to P ≤ .05. Evacuation time lasted on average 87 ± 32 s with a peak heart rate of 184 ± 6 bpm, lactate concentration of 9.4 ± 2.7 mmol/l, and RPE of 17 ± 1. Evacuation time correlated inversely and strongly with anaerobic capacity and power (r = -0.72-0.78, P ≤ .001), but not with aerobic fitness. Inverse and strong correlations were observed between ET and maximal strength variables (r = -0.58-0.69, P ≤ .01), whereas muscular endurance and ET revealed non-significant correlations. Evacuation time correlated moderate to strongly with body fat percentage (r = 0.48, P ≤ .05) and inversely with lean body mass (r = -0.74, P ≤ .001) and body height (r = -0.53, P ≤ .01). The backward regression analysis showed that anaerobic capacity (standardized β = -0.52, P ≤ .001), fat percentage (standardized β = 0.40, P ≤ .001), and isometric leg press (standardized β = -0.25, P ≤ .1) together explained the variance of ET significantly (adjusted R2 = 0.84, P ≤ .001). This study examined thoroughly how different physical fitness dimensions and body composition relate to a CEE test performed by a combination of dragging while crawling and in upright position. Casualty emergency evacuation was discovered as a high-intensity military task, which demands most importantly high anaerobic performance, lean body mass, and maximal strength capabilities. Improving these dimensions of physical fitness should be considered highly important as CEE is essential and possibly one of the most demanding military tasks which every soldier should be able to conduct in combat. From operational perspective, it is relevant that soldiers are able to perform CEE during operations; therefore, further research is needed on how acute operational stress changes the nature of CEE and its physical determinants.