Operational Behavior Research Articles

Fuzzy Assessment Mechanisms under Multi-Objective Considerations

In many operational environments, it is essential to conduct comprehensive minimal assessments of the effects arising from various operational causes, with the goal of achieving effective outcomes. For instance, the aim might be to meet basic production targets in the shortest time possible, using the least cost and minimal labor. Given that actual operational behaviors are often vague and unpredictable, this study proposes a mechanism to assess the minimal effects generated by various operational causes under multi-objective and fuzzy behavior considerations. By considering the relative significance of operational causes or its behaviors under different environments, several weighted extensions are further developed. The mathematical correctness and practical applicability of these assessment mechanisms are analyzed by using an axiomatic characterization.

Hardy–Littlewood maximal operator in a new vanishing Orlicz–Morrey space

We study mapping properties of maximal operator in a new vanishing subspace of Orlicz–Morrey spaces. We show that the vanishing property defining that subspace is preserved under the action of maximal operator. As an application, we also investigate the behavior of fractional operators.

Model Predictive Control of a Stand-Alone Hybrid Battery-Hydrogen Energy System: A Case Study of the PHOEBUS Energy System

Model predictive control is a promising approach to robustly control complex energy systems, such as hybrid battery-hydrogen energy storage systems that enable seasonal storage of renewable energies. However, deriving a mathematical model of the energy system suitable for model predictive control is difficult due to the unique characteristics of each energy system component. This work introduces mixed integer linear programming models to describe the nonlinear multidimensional operational behavior of components using piecewise linear functions. Furthermore, this paper develops a new approach for deriving a strategy for seasonal storage of renewable energies using cost factors in the objective function of the optimization problem while considering degradation effects. An experimentally validated simulation model of the PHOEBUS Energy System is utilized to compare the performance of two model predictive controllers with a hysteresis band controller such as utilized for the real-world system. Furthermore, the sensitivity of the model predictive controller to the prediction horizon length and the temporal resolution is investigated. The prediction horizon was found to have the highest impact on the performance of the model predictive controller. The best-performing model predictive controller with a 14-day prediction horizon and perfect foresight increased the total energy stored at the end of the year by 18.9% while decreasing the degradation of the electrolyzer and the fuel cell.

Comprehensive Measurement and Simulation of Prototype Injection Moulds

The injection moulding industry is dynamically developing. The growing demand for more customizable products can be served by low or middle volume production using prototype moulds and inserts. The conventional material of prototype moulds is aluminum because of its excellent machinability, acceptable strength and stiffness and outstanding thermal conductivity. Prototype moulds are gaining ground in the injection moulding industry, yet their operational behavior (including exact mechanical and thermal process parameters) is largely unknown. We created a comprehensive state monitoring system that measures the operational strain, cavity pressure and temperature of different prototype injection moulds. This way, all important process parameters can be measured and the relations between the moulding parameters and the operational pressure loads, deformations and temperatures can be quantified and analysed.

Research on the Multi-Agent Evolutionary Game Behavior of Joint Operation between Coal Power Enterprises and New Energy Power Enterprises under Government Supervision

Research on the Multi-Agent Evolutionary Game Behavior of Joint Operation between Coal Power Enterprises and New Energy Power Enterprises under Government Supervision

Misses or False Alarms? How Error Type Affects Confidence In Automation Reliability Estimates

Prior research has shown that automation errors—false alarms and misses—differentially impact operator behavior, yet it is not clear why this difference exists. This study examined how the type of automation error, the automation’s reliability, and the number of experiences a person has with an automated system impacts their perception of the system. Participants responded to the correctness of an automation recommendation about the match between pairs of Mega Block shapes while automation reliability, number of trials, and error type varied. At the end of each block, participants provided their estimates of the automation’s reliability, ratings of their confidence in their reliability estimate, and their trust in the system. Our findings indicated that the type of automation error does not impact operator perceptions of the system. Instead, factors such as working memory limitations and pre-existing biases impact these perceptions.

Efficiency-Oriented Model Predictive Control: A Novel MPC Strategy to Optimize the Global Process Performance.

Existing control strategies, such as Real-time Optimization (RTO), Dynamic Real-time Optimization (DRTO), and Economic Model Predictive Control (EMPC) cannot enable optimal operation and control behavior in an optimal fashion. This work proposes a novel control strategy, named the efficiency-oriented model predictive control (MPC), which can fully realize the potential of the optimization margin to improve the global process performance of the whole system. The ideas of optimization margin and optimization efficiency are first proposed to measure the superiority of the control strategy. Our new efficiency-oriented MPC innovatively uses a nested optimization structure to optimize the optimization margin directly online. To realize the computation, a Periodic Approximation technique is proposed, and an Efficiency-Oriented MPC Type I is constructed based on the Periodic Approximation. In order to alleviate the strict constraint of Efficiency-Oriented MPC Type I, the zone-control-based optimization concept is used to construct an Efficiency-Oriented MPC Type II. These two well-designed efficiency-oriented controllers were compared with other control strategies over a Continuous Stirred Tank Reactor (CSTR) application. The simulation results show that the proposed control strategy can generate superior closed-loop process performance, for example, and the Efficiency-Oriented MPC Type I can obtain 7.11% higher profits than those of other control strategies; the effectiveness of the efficiency-oriented MPC was, thereby, demonstrated.

Transient pacing pulse on the T-wave: What is the mechanism?

A patient with a dual-chamber pacemaker for sick sinus syndrome was hospitalized for heart failure. The electrocardiography (ECG) during hospitalization displayed seemingly abnormal pacing artifacts. This report focuses on the problem-solving of an abnormal-looking paced ECG and identifies the pacemaker's operational behavior as the underlying reason.

Evaluation of an experimental prototype in an aerodynamic tunnel with characteristics of a small wind turbine with two blades

The experimental consideration of wind turbines in an aerodynamic tunnel is a powerful alternative to determine the performance of these equipment, both to assimilate their behavior in operation, and to identify constructive and aerodynamic aspects, aiming to convert these characteristics to the real turbine. In the understanding described in this work, the aerodynamic characteristics of the prototype were evaluated, the static torque for the different flow speeds and the power coefficient was estimated based on the concept of variation in the amplitude of movement of the drying when crossing the turbine at different speeds of the flow. The results are compared with the values achieved analytically. The research theory predicted the aerodynamic and structural event, investing numerical and experimental tools. The present work constituted the first experimental event to evaluate the aerodynamic performance of the research project. At this stage, the experimental assessment of static torque was carried out, analyzing the aerodynamic wake of the prototype and determining the RPM curves for the attached wind speeds. The perspective is that it will be possible to describe a new process to, based on the correlation coefficients, determine a curve of the amount of energy granted by a source in a reliable unit of time through simulation or prototyping before starting the survey of real module equipment.

Dynamic risk assessment of Uncertain Random System considering operator's simple emergency-stop action in short time window

Human-machine systems can be considered as typical Uncertain Random Systems (URS). In human-machine systems, operator's simple emergency-stop actions act as a vital soft barrier. Conventional Human Reliability Analyses face challenges in evaluating operator's simple emergency-stop action due to their static characteristics, incompatibility with short time windows, and problems posed by small samples. This paper provides a novel solution to risk assessment of human-machine systems involving operator's simple emergency-stop mechanism. Specifically, an evaluation method of operator's simple emergency-stop action is established, where human cognition is decomposed according to its temporal and logical dimensions, key indicators of human sub-cognition are evaluated, and uncertainty theory is used to integrate these indicators. The output of proposed method is uncertainty of operator's behavior (UOB), which can offer more information than traditional Human Error Probability (HEP) and can be readily converted into uncertainty of human error. Further, a precise simulation method for dynamic risk assessment of Uncertain Random Systems is developed, in which the integration of the UOB is achieved. A case study demonstrates the effectiveness of the proposed methods, and its results show that the proposed methods can clearly reflect the differences in system risk under short time window conditions that have minor distinctions.

Neo banking: A bibliometric review of the current research trend and future scope

Due to evolving consumer expectations and behaviour, rapid technology innovation is transforming the banking sector and forcing banks to shift their operational models and behaviours. Neo banks have significant development potential because of factors like their economic strategy and their growing adoption by millennials. Hence, neo banking has gained significant research attention but there is no bibliometric review on this topic. Therefore, our study addresses academic contribution to neo banking by showcasing research trends and most prominent research streams by conducting a bibliometric analysis in the domain of neo-banking. Our research offers an extensive understanding of neo-banking using bibliometric and thematic analyses. We reviewed 191 relevant articles published between 2009 and 2022 and are extracted from the Scopus database using the PRISMA approach. We used Biblioshiny and VOS viewer to analyse the data and visualize the findings. Our research includes a multi-criteria assessment of prior research, looking at prominent keywords, prolific authors, articles, sources, institutions, and countries. Our study provides valuable insights into prior research and emerging themes by identifying distinct research clusters. It also presents a current overview and proposes future research directions for a continually evolving area. These findings will help the academic researchers to deep dive into this thinly-explored domain.

USE OF TECHNOLOGIES OF HIGHER NERVOUS ACTIVITY AND PSYCHO-PHYSIOLOGICAL HUMAN FUNCTIONS STUDYING IN EXTREME CONDITIONS

Applied techniques and some results of studies the higher nervous activity (HNA) of the people, their psychophysiological functions (PFF) by Ukrainian scientists and doctors were described, as well as influences of extreme conditions on HNA. Aim. Results of the influence of extreme mountain conditions at high altitudes (hypoxia, etc.) demonstration and further research of changes in the psychophysiological functions of the brain under these conditions; description of the developed methods of professional selection. Methods. Comparative analysis of a large number of the data from experiments and observations. Physical, mathematical, program modeling. Methods of HNA, brain research: electroencephalography, diagnosis of personal neurodynamic features, etc. Three methods of PFF research: parameters of the neurodynamic level, parameters of the neuropsychological level, and personal specifics. The adapted questionnaire scheme (QS) based on Cattell's 16-factor personality tests was applied. Results. The influence of hypoxia and other factors of mountain conditions on HNA were studied deeply. The results were presented. Also, there were presented results of registered changes of EEG in such extreme conditions. The influence of a number of stress factors in extreme conditions (hypoxia, etc.) has been demonstrated. Some basic methods of HNA researches used in such conditions were described as well as results of investigations of individual typological features of the nervous systems were presented. Methods for human psychophysiological functions studying were described. Studies of human personal characteristics were described in details. Data recorded by the PNN-3 device were taken for the diagnosis of personal neurodynamic features. The parameters of the neuropsychological level were determined using the following methods: "triangles" (the level of development of short-term visual memory), "instrument scales" (working memory, attention functions, etc.), and "red and black tables" (allocation and switching of attention). Personality structures, features, and types of behavior of operators in stressful situations were estimated basing on adapted QS by Cattell. Mathematical models of the reliability of human nervous system functioning under extreme conditions were developed. Conclusions. The obtained results were taken as the basis for the developed professional selection methods for special contingents, pilots, operators, etc. Physical, mathematical, and program models of the reliability of the human nervous system functioning in these conditions were proposed.

A missing data processing method for dam deformation monitoring data using spatiotemporal clustering and support vector machine model

Deformation monitoring is a critical measure for intuitively reflecting the operational behavior of a dam. However, the deformation monitoring data are often incomplete due to environmental changes, monitoring instrument faults, and human operational errors, thereby often hindering the accurate assessment of actual deformation patterns. This study proposed a method for quantifying deformation similarity between measurement points by recognizing the spatiotemporal characteristics of concrete dam deformation monitoring data. It introduces a spatiotemporal clustering analysis of the concrete dam deformation behavior and employs the support vector machine model to address the missing data in concrete dam deformation monitoring. The proposed method was validated in a concrete dam project, with the model error maintaining within 5%, demonstrating its effectiveness in processing missing deformation data. This approach enhances the capability of early-warning systems and contributes to enhanced dam safety management.

A smart look at monitoring while drilling (MWD) and optimizing using acoustic emission technique (AET)

Monitoring while drilling (MWD) is a crucial task in mining operations. Accurately measuring drill and rock-related operating parameters can significantly reduce the cost of drilling operations. This study explores the potential of monitoring drilling specific energy (SE) and optimizing drilling operations by processing vibroacoustic signals generated while drilling. For this purpose, 30 samples of different rocks, are used for drilling tests. During the drilling process, the acoustic and vibration signals are recorded and analyzed in the time, frequency, and time–frequency domains., and parameters related to the resulting spectra are extracted. After obtaining the vibroacoustic parameters for drilling, the relationship between them and the drilling SE was investigated. There is evidence that the progression of SE contributes to the magnitude of rock drilling vibroacoustic features, which could be employed to indicate energy conditions during drilling. Results obtained in this study have the potential to be used as the basis for an industrial monitoring system that can detect excessive energy consumption and advise the user of the end of the bit's useful life. This method can be an intelligent technique for measuring the behavior of real-time drilling operations based on the SE simply by installing vibroacoustic sensors on the drilling machines.

Performance During a Task That Simulates Passive Sonar Operator Duties Under Conditions of Varying Workloads.

It is critical to develop and implement lab-based computer experiments that simulate real-world tasks in order to characterize operational requirements and challenges or identify potential solutions. Achieving a high degree of laboratory control, operational generalizability, and ease-of-use for a task is challenging, often leading to the development of tasks that can satisfy some facets but not all. This can result in insufficient solutions that leave real-world stakeholders with unsolved problems. This issue is addressed using a customized passive sonar simulator application that provides extensive researcher control over the design and manipulation of a sonar task; a visual appearance and cognitive demand similar to a true submarine-based sonar task; and a convenient and short training routine for sonar novices. The task requires participants to watch for multiple signal sources of varying appearance and salience and subsequently classify these signals into their respective categories. The current study investigated the effects of stimulus signal strength and signal density on sonar task performance-including metrics of classification accuracy, classification confidence, and response times-finding an interaction between signal density and signal strength that resulted in greater performance errors with high signal density at the weakest signal strength. The lab-based sonar application provides new possibilities for research, not limited to signal intensity and signal density but also through the manipulation of parameters such as the number of unique targets, target appearance, and task duration. This application may illuminate the operational demands that each of these factors may have on operator behavior within the dynamic tasks.

Leveraging multi-zone building data with machine learning-based models and genetic algorithms to optimize air handling units

Optimizing air handling units (AHUs) in multi-zone buildings presents significant challenges. As buildings become more complex, the demand for tailored temperature control across various zones becomes paramount. This study leverages multi-zone building data with machine learning-based models and optimization techniques to optimize AHUs by specifically integrating deep neural network (DNN) modeling, clustering analysis, and a genetic algorithm (GA). We developed 18 models to predict AHU supply air temperature (Tsa) and 2 models to predict chiller power consumption (P) using DNN. Clustering analysis was applied to the return air temperature (Tra) of each AHU, serving as initial conditions for the GA. The clustering analysis provided insights into the AHU operational behavior, enhancing the optimization process precision. The GA's objective function maintained the AHUs' Tsa and minimized P by adjusting parameters such as valve openings, fan frequencies, chilled water supply temperature, and cooling water flowrate. The results indicated that DNN models demonstrated high predictive accuracy, with 16 models showing an R2 higher than 0.96. The results suggested that AHU411 requires increased capacity during high Tra condition, while AHU212 needs an enhanced model with more diverse training data or the incorporation of additional influencing factors. Validation revealed that this approach improved temperature maintenance across zones, with 96 % of the data falling within demand temperature range (Tset), and achieving Tset required 41 % higher power input.

Mechanical Behavior of Sediment-Type High-Impurity Salt Cavern Gas Storage during Long-Term Operation

With the development of salt cavern gas storage technology, the construction of large-scale salt cavern gas storage using sediment voids is expected to solve the problems of low effective volume formation rate and poor construction economy of high-impurity salt mines. At present, there are few studies on the long-term operational mechanical behavior of salt cavern gas storage under the influence of sediment accumulation. The present paper studies the influence of sediment height, particle gradation, and operating pressure on the stability of salt caverns by constructing a coupling model of sediment particle discontinuous medium and surrounding rock continuous medium. The continuous–discontinuous coupling algorithm is suitable for analyzing the influence of sediment height and particle gradation on the creep shrinkage of salt caverns. The increase in sediment height slows down the creep shrinkage of the cavern bottom, which strengthens the restraining effect on the surrounding rock of the cavern. As a result, the position of the maximum displacement of the surrounding rock moves to the upper part of the cavern. The sediment particle gradation has little effect on the cavern volume shrinkage rate. The greater the coarse particle content, the smaller the cavern volume shrinkage rate. The greater the operating pressure, the more conducive to maintaining the stability of the cavern. This situation slows down the upward movement of the sediment accumulation and increases the gas storage space in the upper part of the cavern. The obtained results can provide a reference for evaluating the long-term operational stability of sediment-type high-impurity salt cavern gas storage.

Best evidence summary for aspiration prevention and management in critically ill patients with nasogastric feeding.

To evaluate and summarize the available evidence on the prevention and management of nasogastric aspiration in critically ill patients to inform the development of evidence-based clinical practice. This study was an evidence summary according to the evidence summary reporting standard of the Fudan University Center for Evidence-Based Nursing. According to the '6S' model of evidence resources, evidence on the prevention and management of aspiration in critically ill patients on nasogastric feeding was retrieved, including clinical decision-making, best practices, guidelines, evidence summaries, expert consensus and systematic evaluations. UpToDate, BMJ Best Practice, JBI, National Guideline Clearing-house, Guidelines International Network, Scottish Intercollegiate Guidelines Network, National Institute for Health and Care Excellence, Registered Nurses Association of Ontario, Yi Mai tong Guidelines Network, the Cochrane Library, PubMed, Web of Science, Embase, OVID, Sinomed, CNKI, Wan Fang database. The search period was from January 2013 to June 2023. We included a total of 30 high-quality articles and summarized 36 pieces of evidence from them. These pieces of evidence covered 11 dimensions of multidisciplinary management, aspiration risk assessment, tube location, nutritional infusion management, position management, airway management, and oral hygiene. The level of evidence in the study was predominantly level 1 and level 5, with 27 pieces of evidence recommended as 'strong' and 9 pieces of evidence recommended as 'weak'. This study summarizes 36 pieces of evidence on preventing and managing aspiration in critically ill patients with nasogastric feeding. But the characteristics of hospitals should be considered in the application of future evidence. Aspiration is the most serious complication during nasogastric feeding, which seriously affects the prognosis of patients. Preventing and managing aspiration in nasogastric patients has proven to be a challenging clinical problem. This study summarized 36 pieces of best evidence in 11 dimensions, including multidisciplinary team, assessment and identification, line position, feeding management, and so on. The implementation of these evidences is conducive to standardizing the operation behaviour of nasogastric feeding in clinical medical staff and reducing the occurrence of aspiration. This research followed the evidence summary reporting specifications of the Fudan University Center for Evidence-based Nursing. The registration number is 'ES20221368'.

Efficient and Secure Management of Medical Data Sharing Based on Blockchain Technology

In the current landscape of medical data management, processing data across diverse institutions and maximizing their value are paramount. However, traditional methods lack a secure and efficient mechanism for end-to-end traceability and supervision, posing challenges in distributed scenarios lacking mutual trust. Leveraging blockchain’s decentralized, tamper-proof, and traceable features, this paper introduces a blockchain-based medical data management platform. This platform enables full-process management of raw data, operational behaviors, intermediate data, and final data, meeting the needs of trusted storage and supervision of data. We propose two methods, namely, naive method and DAG-based method, to realize forward tracking and backward tracing of medical data stored on the blockchain, respectively. We validated and analyzed the storage and query performance of the medical data management platform on real medical data, and we also conducted experimental analyses on the efficiency of the proposed traceability algorithm under different data scales and processing path lengths. The results demonstrate that our platform and traceability methods effectively meet the management needs of medical data distributed across institutions.

Windows: socio-environmental dimensions in Palestinian residential buildings

People spend a significant portion of their lives indoors. Nowadays, windows are the essential architectural element that allows users to have contact with the outside world. This contact has an important impact on our physiology, psychology, well-being, and indoor environment. Understanding the physical and behavioral (social) characteristics of this element in the Palestinian residential building is still insufficiently explored. A cross-sectional survey of 272 respondents was conducted to investigate the openings’ characteristics and user’s behavior to assess their influence on residents’ satisfaction and indoor performance. This assessment was based on the concept that residents’ satisfaction with their homes is a measure of buildings’ performance in meeting users’ needs, expectations, and aspirations. The findings show that the physical properties (i.e. Window wall ratio, Window floor ratio, position, orientation, etc.) of windows do not meet the minimum threshold of sustainable and energy-efficient values (i.e. Daylight, thermal comfort). In addition, the survey analysis determines the driving parameters and their corresponding variations influencing window operations in different periods of the day and season. The culture plays a central role in the Palestinians’ window operation behavior.