Operational Level Research Articles

A qualitative exploration of the coordinator’s role in an intersectoral childhood overweight prevention programme in the Netherlands: ‘a lot is expected from one person’

BackgroundIntersectoral collaboration and its coordination are vital for community health promotion. Given the diverse organisational contexts in which local coordinators build intersectoral collaboration, training and support needs of coordinators may vary widely. To date, there is limited insight into how coordinators tasked with building intersectoral collaboration apply their role given their specific organisational context. A more detailed understanding of this process will provide valuable guidance for training and supporting local coordinators. In the current study we focussed on coordinators involved in building intersectoral collaboration within the ‘Healthy Youth, Healthy Future’ (JOGG) approach in the Netherlands. The organisational contexts in which these local coordinators operate vary considerably. The aim of this study was to explore how local coordinators of the JOGG approach apply their role in building intersectoral collaboration and the competencies they require, taking into account their organisational context.MethodsWe conducted interviews with twelve local JOGG coordinators and two focus groups with eight community advisors from the national JOGG organisation. Data was analysed both inductively and deductively.ResultsJOGG coordinators appeared to take on seven different roles over time: implementer, project manager, networker, matchmaker, linchpin, politician and programme manager. These roles required different competencies and varied according to the organisational context, including: available resources, the position of the employing organisation in existing local stakeholder networks, the coordinators’ responsibilities in their employing organisation and professional background. In addition, the coordinators role depended on the implementation phase of the JOGG approach. During the first phase, roles at the operational level were more prominent, since they were important for engaging stakeholders and facilitating collaboration. In later phases, coordinators took on roles at a tactical and strategic level in order to mobilise their network.ConclusionsThis study highlights the diversity in how JOGG coordinators apply their role. Our findings highlight the importance of carefully selecting the organisation where coordinators are employed, as this influences their possibilities. In addition, our study provides directions for recruiting coordinators for an intersectoral health promotion approach and supporting them, taking into account the phase of the approach and organisational context.

An LSTM network-based genetic algorithm for integrated procurement and scheduling optimisation

Modern supply chains are characterised by high complexity, requiring effective management through coordinated activities across interrelated functions. This study aims to move from isolated optimisation to integrated decision-making, which offers new potential for efficiency. We investigate an integrated procurement-production problem based on a real case study from a German company specialising in printed circuit board assembly. We propose a novel solution approach that combines a genetic algorithm with a neural network to increase computational efficiency. Our comprehensive evaluation scheme demonstrates the viability of the approach in generating integrated decisions within a limited time frame. Specifically, we quantify the benefits of integrated over separated decision-making at the operational level, extending previous research focussed on the tactical level. The results indicate considerable benefits of integrated decision-making across a wide range of cost factors, although the exact savings depend on specific cost parameters. In addition, we evaluate our model on a rolling horizon planning basis, which is crucial for modelling realistic supply chain behaviour and remains underrepresented in the literature.

Experimental Tests and Simulations About The Efficiency of Commercial Hybrid Inverters Operating at Variable Power Factor

The need to ‘rethink’ the concept of Distribution, both at the planning and operational levels, arises from the emergence of the Distributed Generation paradigm, mostly installed in LV networks. The existing arrangements for the management, protection and control of distribution networks are typically inadequate for this ever-increasing presence of Distributed Generation. Consequently, national and international grid codes have been updated requiring distributed generators to be involved in grid control by supplying ancillary services, such as the voltage and frequency regulation. In this context, the Italian Standards, and in particular the CEI 0–21, require hybrid inverters of residential systems, which are usually only setup to supply active power at unity power factor, to include also the possibility of being able to absorb or supply reactive energy. This allows to limit the over / under voltages problems. To this aim, the inverter manufacturers have introduced the possibility for residential inverters to set the power factor. These new capabilities have been exploited in this paper in order to study the inverter performance with the variation of the power factor, considering both the inductive and the capacitive behaviour. In particular, the presented paper focuses on experimental tests on a hybrid inverter-based system for residential use with the aim of evaluating the dependence of the inverter efficiency on the power factor. Based on measured values, a Matlab/Simulink simulator has been developed for modelling the system, using the found dependence. The main aim is to evaluate the inverter control systems in order to participate in regulation services and to evaluate the inverter efficiency in case of a power factor different from unity.

Unravelling firm performance in evolving markets: a capabilities approach to China's automotive sector

ABSTRACT This study investigates how operational and dynamic capabilities have influenced the adaptation and performance of Chinese automakers in response to industry shifts toward electrification and intelligentisation from the mid-2010s onward. Focusing on XPeng Motors, Jeep China, and BYD, the research examines how varying operational capabilities levels, categorised as baseline, standard, and VRIN (Valuable, Rare, Inimitable, Non-substitutable) resources, interact with dynamic capabilities to shape strategic responses in a rapidly evolving market. Using a mixed-methods approach that includes secondary data analysis, participatory observation, and expert interviews, this study highlights the significance of aligning operational and dynamic capabilities to achieve sustained competitive advantages. Findings reveal that robust operational capabilities amplify the effectiveness of dynamic capabilities, allowing firms like BYD to adapt and thrive in volatile environments, while firms with weaker foundations, like XPeng, struggle to scale and sustain. The research contributes to strategic management literature by clarifying resource-capability alignment and offering insights for firms navigating disruptive industry changes.

Thermal and flow optimization and generative design simulations of the curing press manifold used in tire production

The tire industry involves complex processes that require high temperatures and pressures for tire production and processing. In these processes, rubber dough is placed in molds using baking presses and shaped under high temperature and pressure. Manifold blocks are used to feed the molds in these presses and to ensure equal temperature distribution between the molds. However, existing manifold blocks tend to deform in a short time under high temperature and pressure and require constant maintenance. These changes can affect production continuity, reduce production quality and increase maintenance costs. Therefore, there was a need to research a more durable and low-maintenance manifold solution. In this study, Thermal Flow analysis was performed on the Cooking Press Manifold using the “Generative Design” method and the appropriate operating level of the system was determined.

A Safety Evaluation Method for Converter Station Operation Based on Dynamic Fuzzy Theory

In order to accurately evaluate the safety risk level of converter station operations and reflect its changing trends, an evaluation method based on dynamic fuzzy theory is proposed. By constructing an initial Work Breakdown Structure-Risk breakdown structure (WBS-RBS) coupled matrix, identifying risk factors, and using the vague set screening method to screen out key risk factors, a comprehensive safety evaluation index system for converter station operations is established. The dynamic fuzzy values of all levels of evaluation indicators are calculated using dynamic fuzzy theory, intuitively reflecting the risk level and its changing trends of all levels of evaluation indicators. Taking the Suzhou ±800 kV converter station project as an example to verify this method, the results show that the safety risk level of this converter station operation is medium–low and tends to be low. This method can objectively reflect the ambiguity and randomness of risk evaluation, improve evaluation accuracy, and intuitively display the risk-changing trends, providing a reference for similar projects.

Institutional analysis of water governance in the Colorado River Basin, 1922–2022

The 1922 Colorado River Compact started the long history of water governance in the Colorado River Basin. Over the last century, the institutional structure has shaped water governance in the basin. However, an understanding of the long-term evolution is lacking. This study examines how water management strategies have evolved at the basin scale by incorporating institutional, temporal, and network structure analysis methods to examine long-term changes. Content analysis was employed to systematically investigate encouraged and/or discouraged water management actions at different rule levels. The water governance network was examined at four points in time to map the institutional structure, actors, and governance level at which rules are issued and targeted. Using institutional analysis, we found constitutional, operational, and collective-choice level rules for water supply, storage, movement, and use have been altered via layering of new governance rules without major rule or responsibility alteration. The network analysis results indicate that key decision-making positions have remained and actors who issue and are targeted by the rules lack significant change. We found original positions of power have been maintained, potentially stagnating the space for problem-solving and management strategy renegotiation. Our results indicate that path dependency has shaped water governance and who is able to influence decision-making.

A Soft Start Method for Doubly Fed Induction Machines Based on Synchronization with the Power System at Standstill Conditions

Due to their exceptional operational versatility, doubly fed induction machines (DFIM) are widely employed in power systems comprising variable renewable energy-based electrical generation sources, such as wind farms and pumped-storage hydropower plants. However, their starting and grid synchronization methods require numerous maneuvers or additional components, making the process challenging. In this paper, a soft start method for DFIM, inspired by the traditional synchronization method of synchronous machines, is proposed. This method involves matching the frequencies, voltages, and phase angles on both sides of the main circuit breaker, by adjusting the excitation through the controlled power converter at standstill conditions. Once synchronization is achieved, the frequency is gradually reduced to the rated operational levels. This straightforward starting method effectively suppresses large inrush currents and voltage sags. The proposed method has been validated through computer simulations and experimental tests, yielding satisfactory results.

Supply Chain Stability and Enterprises’ Total Factor Productivity: From the Perspective of Development Sustainability

Because of increasing global complexities and the frequent occurrence of black swan events, the risk of supply chain disruptions intensifies, and the sustainability of enterprise development faces significant challenges. By focusing on supply chain security and aiming for sustainable enterprise development, this study explores how stable supply chains contribute to enhanced productivity of core enterprises, using the theory of social capital as a framework. An empirical analysis was conducted using a sample of A-share listed companies in Shanghai and Shenzhen, China, from 2009 to 2021. The research findings indicate that greater supply chain stability is associated with higher total factor productivity in enterprises. The mechanism test results show that the supply chain stability relationship can improve the total factor productivity of enterprises through two paths, such as improving the operation and management level of enterprises and optimizing resource allocation. After further heterogeneity analysis, it is found that the stable relationship of the supply chain has a stronger positive impact on the total factor productivity of core enterprises in the non-state-owned enterprise group, the eastern enterprise group, and the large-size enterprise group. These findings help to provide insights for enterprises to achieve sustainable development in the new era.

Measuring social movement engagement: A co-creational approach to public engagement and social capital

The research sets out the measurement of three levels of social movement engagement (i.e., informational, relational, and societal engagement) and tests a social movement engagement model. At the operational level, the research extends Johnston and Taylor’s (2018) three tiers of engagement. The model suggests that social movement organizations facilitate opportunities to increase members’ relational engagement because it enhances societal engagement and the production of social capital bonding.

A comprehensive approach to building a continuous hydrologic model considering soil moisture using Earth Observation data

ABSTRACT In recent years, both availability and interest in Earth Observations (EO) have increased due to their ability to provide information with extensive spatial coverage, which is valuable for data-scarce regions. This study provides a roadmap to exploit EO/satellite data (EO-based model) for continuous hydrological simulation using the Hydrologic Engineering Center–Hydrologic Modelling System model with a soil moisture accounting (SMA) component. As a case study, we consider the Boeotikos Kephisos River basin, in Greece. The SMA component is calibrated using the HiHydroSoils dataset, to map its parameters to the regionally varying soil hydraulic properties and a comparison is made to an alternative parameterization, following the standard literature approach (literature-based model). The effectiveness of satellite data in enhancing model performance is further assessed, by comparing three different satellite precipitation datasets, as model drivers, and by using satellite-based soil moisture for model initialization. The discussion extends to the potential for integration of EO/satellite data at the operational level, by simulating a significant precipitation event. Yet, the most promising result pertains to the opportunity to exploit satellite-derived estimates of soil hydraulic properties to base the calibration of the data-intensive SMA scheme, with the EO-based model significantly outperforming the literature-based model parameterization.

Simulation-based optimization of decision-making process in railway nodes

Abstract Smooth operation of railway stations and yards is vital for the efficient functioning of the whole railway system. Being complex systems, their operation is extremely sensitive to various influences, which makes their management, especially at the operational level, very difficult. Efficient tools to aid the decision-making process of dispatchers of such stations are therefore needed. With an emphasis on increasing the effectiveness of decision support tools, we propose a simulation-based optimization algorithm. This algorithm extracts a dataset from a simulation model and then reduces it to a partial dataset to be able to use specific exact optimization method in operational management. The partial dataset is limited by certain time horizon. The applicability of the proposed algorithm has been verified on two distinct tasks, namely, personnel assignment and service task assignment in a maintenance depot, confirming the usability of the proposed approach.

Adaptive crisis management at the operational level: Responses to COVID-19 in the Australian resources sector

Abstract The COVID-19 pandemic in 2020 significantly impacted Australia’s resources sector, particularly mining, oil, and gas industries, posing challenges for operational leaders. This study applied Adaptive Crisis Management Theory (ACMT) to understand how these leaders adapted during the crisis. Through interviews with 32 operational leaders, it was found that their roles evolved as crisis demands changed. Initially, they addressed immediate needs, then shifted focus to remote work facilitation and digital transformation, and finally emphasised recovery, trust, and resilience. These adaptations influenced leaders’ behaviours, highlighting the importance of flexibility in supporting employee wellbeing and organisational continuity during crises.

Promoting best practices in ocean forecasting through an Operational Readiness Level

Predicting the ocean state in a reliable and interoperable way, while ensuring high-quality products, requires forecasting systems that synergistically combine science-based methodologies with advanced technologies for timely, user-oriented solutions. Achieving this objective necessitates the adoption of best practices when implementing ocean forecasting services, resulting in the proper design of system components and the capacity to evolve through different levels of complexity. The vision of OceanPrediction Decade Collaborative Center, endorsed by the UN Decade of Ocean Science for Sustainable Development 2021-2030, is to support this challenge by developing a “predicted ocean based on a shared and coordinated global effort” and by working within a collaborative framework that encompasses worldwide expertise in ocean science and technology. To measure the capacity of ocean forecasting systems, the OceanPrediction Decade Collaborative Center proposes a novel approach based on the definition of an Operational Readiness Level (ORL). This approach is designed to guide and promote the adoption of best practices by qualifying and quantifying the overall operational status. Considering three identified operational categories - production, validation, and data dissemination - the proposed ORL is computed through a cumulative scoring system. This method is determined by fulfilling specific criteria, starting from a given base level and progressively advancing to higher levels. The goal of ORL and the computed scores per operational category is to support ocean forecasters in using and producing ocean data, information, and knowledge. This is achieved through systems that attain progressively higher levels of readiness, accessibility, and interoperability by adopting best practices that will be linked to the future design of standards and tools. This paper discusses examples of the application of this methodology, concluding on the advantages of its adoption as a reference tool to encourage and endorse services in joining common frameworks.

Application of Distributed Collaborative Optimization in Building Multi-Energy Complementary Energy Systems

This article investigates the application and physical mechanism exploration of distributed collaborative optimization algorithms in building multi-energy complementary energy systems, in response to the difficulties in coordinating various subsystems and insufficient dynamic control strategies. On the basis of modeling each subsystem, the Dual Decomposition algorithm is used to decompose the global optimization problem of the system into several independent sub problems, achieving independent optimization of each subsystem. Through an adaptive dynamic scheduling strategy, real-time data and predictive information are continuously updated and controlled, effectively allocating system resources. The experimental results show that compared to the original system before optimization, the improved algorithm in this paper reduces the total energy consumption of the system by 6.9% and 2.8% on typical summer and winter days, respectively. The conclusion shows that the algorithm proposed in this paper can effectively solve the problem of system coordination difficulties, improve system resource allocation and overall operation level, and provide a new perspective for the optimization design and operation control of energy systems.

Comprehensive approach to static firing tests of micro gas turbine engines powered by liquid fuels

The paper presents test results on the combustion of liquid fuels in micro gas turbine engines (MGTE). A setup was designed and built to determine the following MGTE characteristics: thrust, inlet static pressure, compressor static pressure, compressor total pressure, combustor total pressure, turbine total pressure, turbine speed, and the air temperature at the inlet, inside the compressor, at the turbine outlet, and at the nozzle exit. Thermodynamic cycle analysis of MGTEs was performed in the operation mode providing the required thrust. Noise and vibration levels of the MGTE operation were measured using a noise and vibration analyzer. Concentrations of anthropogenic emissions (CO, CO2, NO, NO2, N2O, SO2, CH4, C3H8) were recorded using a set of sensors. The tests revealed consistent patterns in the variation of throttle characteristics, gas composition, noise, and vibration in different engine operation modes. The test results were processed to produce plots of the key MGTE characteristics. Recommendations were developed for testing new types of fuels in MGTEs.

Energy Consumption and Fume Analysis: A Comparative Analysis of the Blasting Technique and Mechanical Excavation in a Polish Gypsum Open-Pit Mine

This article presents a comparative assessment of energy consumption and fume emissions such as NOx, CO2, and CO associated with the excavation of a specified gypsum volume using two mining methods (blasting and mechanical extraction). The analysis was carried out based on a case study gypsum open-pit mine in Poland where both extraction methods are applied. The findings indicate that, for the same output volume, blasting operations require significantly less energy (ranging from 1298.12 MJ to 1462.22 MJ) compared to mechanical excavation (86,654.15 MJ). Furthermore, a substantial portion of the energy in blasting operations is attributed to explosive loading and drilling (970.95 MJ). Conversely, mechanical mining results in higher fume emissions compared to blasting. However, during mechanical extraction, the fumes are dispersed over a prolonged period of 275 h, whereas blasting achieves the same gypsum volume extraction in approximately 7.5 h. The prediction model suggests that, based on the obtained data, overall gypsum extraction will decline unless new operational levels are developed or the mine is expanded. This reduction in gypsum extraction will be accompanied by a corresponding decrease in energy consumption and emission of fumes.

Specific road safety issues in LMICs: an overview and some illustrative examples

This paper gives an overview of the work of PIARC Working Group 3.1.1 ‘Specific road safety issues for LMICs’. The working group performed its activities in the period 2019–2023. We prepared two deliverables: (a) a literature review, and (b) an overview of illustrative examples. The review started from the notion that the road safety problem requires a multi-disciplinary approach. The safe system approach is generally considered as the central concept for this purpose and this starting point is also taken in this study. However new directions are needed to make the safe system concept work in LMICs. The period of the first UN Decade of Action for Road Safety has brought us a series of valuable problem analysis and overview articles prepared by a variety of institutions and institutes. As a PIARC working group we did not repeat this effort, but used it as a starting point to indicate which specific issues do require a boost in LMICs for the coming period up to 2030. We concluded that the following 12 issues deserve special attention. Strategical: (i) Sustainable Development Goals integral approach, (ii) safety culture, (iii) road safety management and leadership, (iv) building road safety expertise and science; Tactical: (v) transportation system as a whole, (vi) city design, architecture, land use, rural planning, (vii) cost effectiveness, (viii) legislation and enforcement; Operational: (ix) speed, (x) sustainable safe roads, (xi) vehicles as a safe system component, (xii) post-crash health care. As a result of our discussions and analyses we also concluded that it is worthwhile and necessary to make a distinction between the issues in terms of levels of approach. Making roads and vehicles safe may be considered as operational safety measures on a component level, whereas city design and transport system issues do represent a more tactical approach. On top of that, organisational and cultural aspects do have a more strategical nature. As in many managerial and planning tasks the distinction between strategical, tactical and operational levels of approach is needed in the road safety field. It illustrates that the Safe System concept asks for a multi-level vision, thus preventing a silo approach with a limited focus on human behaviour, safe roads or vehicle safety. A further analysis for each of the selected issues resulted in priority areas, i.e. topics that deserve special attention in the LMIC context. In a similar line of reasoning we also described illustrative examples, i.e. LMIC related before-after studies that show the perspective of certain measures on an evidence basis. Although we found some illustrative cases for each of these issues, our search for evidence based cases confirmed the findings from recent overview articles indicating the lack of LMIC related road safety research. A more widespread implementation of effective road safety measures in LMICs would require a stronger national commitment and leadership from the road safety agencies point of view in the first place. Moreover an evidence based policy asks for a strong national and regional knowledge infrastructure. Ultimately road safety policies and road safety research programs are to be considered as inseparable. A strong local knowledge infrastructure may thus become the basis for an effective national road safety policy.

Research on digital twin technology and its application in intelligent operation and maintenance of high-speed railway infrastructure

PurposeThis paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.Design/methodology/approachThis paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design.FindingsDigital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.Originality/valueThis paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

Application of Traffic Cone Target Detection Algorithm Based on Improved YOLOv5.

To improve the automation level of highway maintenance operations, the lightweight YOLOv5-Lite-s neural network was deployed in embedded devices to assist an automatic traffic cone retractor in completing recognition and positioning operations. The system used the lightweight shuffle Net network as a backbone for feature extraction, replaced convolutional layers with focus modules to reduce computational complexity, and reduced the use of the C3 layer to increase network speed, thereby meeting the speed and accuracy requirements of traffic cone placement and retraction operations while maintaining acceptable model inference accuracy. The experimental results show that the network could maintain recognition accuracy and speed values of around 89% and 9 fps under different working conditions such as varying distances, lighting conditions, and occlusions, meeting the technical requirements for deploying and retrieving cones at a speed of 30 cones per minute when the operating vehicle's speed was 20 km/h. The automatic traffic cone placement and retraction system operated accurately and stably, achieving the application of machine vision in traffic cone retraction operations.