Operational Behavior Research Articles

What motivates the choice to custom hire pest management spraying services?

This article presents a model of how farmers choose to custom hire for pest control. The decision-making process is illustrated through a discrete choice experiment conducted via a pilot survey of soybean growers in Michigan, Illinois, and Indiana. Farmers responded to a hypothetical pest infestation by choosing between custom operators, spraying on their own, or leaving the field to its fate. Among farmers who choose to spray, the mean willingness to pay for marginal increases in timeliness (as defined as the chance of late spraying) ranges from 37 to 52 cents per acre. We also find that farmers more averse to risk are more sensitive to custom operator timeliness and that farmers with better-developed social networks are less sensitive to the risk of delay. The results of this study can motivate future research into the drivers of on-farm decision-making, especially as it relates to custom hire behavior in pest control and other field operations. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Assessing assembly instructions quality using operator behavior

Assessing assembly instructions quality using operator behavior

Design of A PFR For the Production of 1,000,000 Tons Per Year of Ethyl Acetate from Esterification of Acetic Acid and Ethyl Alcohol

The research considered the design or size of a plug flow reactor for the production of 1,000,000 tons of ethyl acetate per year from the esterification of acetic acid and ethyl alcohol in the presence of an acid catalyst. The PFR design models for volume, height, diameter, space time, space velocity, quantity of heat generated, quantity of heat generated per unit volume of the reactor as well as the temperature effect models were developed using the conservation principle of mass and energy at steady state operation of the reactor. The developed models were simulated using MATLAB at initial feed and operating temperature of 299.830k and 343.15k respectively and fractional conversion variation between 0 to 0.95 at an interval of 0.05. At a maximum conversion of 0.95, the PFR size specification for volume, height, diameter, space time, space velocity, quantity of heat generated and the quantity of heat generated per unit volume of the reactor was 15.2774m3, 4.2691m, 2.1346m, 2.9956sec., 0.3338sec-1, 12821.5800j/s and 839.2536j/sm3 respectively. The effect of the operating parameters on the performance or functional parameters of the reactor are presented in profiles as shown in figure 2 to 12 and the profile behaviour or trend were in agreement with process behaviour of PFR steady state operation in various literatures. The research have shown that in order to ensure sustainability and continuous production of ethyl acetate to meet the global demand of the economic and viable product, the plug flow reactor have demonstrated a good performance characteristics as a reacting media for the esterification process especially in the energy efficiency of the process as well as the product yield.

Krylov complexity of fermion chain in double-scaled SYK and power spectrum perspective

We investigate Krylov complexity of the fermion chain operator which consists of multiple Majorana fermions in the double-scaled SYK (DSSYK) model with finite temperature. Using the fact that Krylov complexity is computable from two-point functions, the analysis is performed in the limit where the two-point function becomes simple and we compare the results with those of other previous studies. We confirm the exponential growth of Krylov complexity in the very low temperature regime. In general, Krylov complexity grows at most linearly at very late times in any system with a bounded energy spectrum. Therefore, we have to focus on the initial growth to see differences in the behaviors of systems or operators. Since the DSSYK model is such a bounded system, its chaotic nature can be expected to appear as the initial exponential growth of the Krylov complexity. In particular, the time at which the initial exponential growth of Krylov complexity terminates is independent of the number of degrees of freedom. More generally, and not limited to the DSSYK model, we systematically and specifically study the Lanczos coefficients and Krylov complexity using a toy power spectrum and deepen our understanding of those initial behaviors. In particular, we confirm that the overall sech-like behavior of the power spectrum shows the initial linear growth of the Lanczos coefficient, even when the energy spectrum is bounded.

Automated Evaluation Method for Risk Behaviors of Quay Crane Operators at Ports Using Virtual Reality

Currently, the operational risk assessment of quay crane operators at ports relies on manual evaluations based on experience, but this method lacks objectivity and fairness. As port throughput continues to grow, the port accident rate has also increased, making it crucial to scientifically evaluate the risk behaviors of operators and improve their safety awareness. This paper proposes an automated evaluation method based on a Deep Q-Network (DQN) to assess the risk behaviors of quay crane operators in virtual scenarios. A risk simulation module has been added to the existing automated quay crane remote operation simulation system to simulate potential risks during operations. Based on the collected data, a DQN-based benchmark model reflecting the operational behaviors and decision-making processes of skilled operators has been developed. This model enables a quantitative evaluation of operators’ behaviors, ensuring the objectivity and accuracy of the assessment process. The experimental results show that, compared with traditional manual scoring methods, the proposed method is more stable and objective, effectively reducing subjective biases and providing a reliable alternative to conventional manual evaluations. Additionally, this method enhances operators’ safety awareness and their ability to handle risks, helping them identify and avoid risks during actual operations, thereby ensuring both operational safety and efficiency.

Engineering of hyperentangled complex quantum networks

Abstract We propose a novel scheme to engineer the atomic hyperentangled cluster and ring graph states invoking cavity-QED technique for applicative relevance to quantum biology and quantum communications utilizing the complex quantum networks. These states are engineered using both external quantized momenta states and energy levels of neutral atoms under off-resonant and resonant Atomic Bragg Diffraction (ABD) technique. The study of dynamical capacity and potential efficiency have certainly enhanced the range of usefulness of these states. In order to assess the operational behavior of such states when subjected to a realistic noise environment has also been simulated, demonstrating long enough sustainability of the proposed states. Moreover, experimental feasibility of the proposed scheme has also been elucidated under the prevailing cavity-QED research scenario.

Optimal power generation of proton exchange membrane fuel cell using ANFIS based MPPT algorithm

Fuel cells are the most promising energy source for the future energy demand. The automobile industry is looking at the integration of fuel cells with electric vehicles (EV). This integration comes with many challenges like dynamic operational behaviors. For operating the fuel cell with maximum efficiency, this work proposes an Adaptive Neuro Fuzzy Inference System (ANFIS) based Maximum Power Point Tracking (MPPT) method. The hydrogen flow rate, pressure and stack temperature are the parameters considered to track the maximum power point of the fuel cell. The ANFIS-MPPT algorithm has been integrated with the 1.26 kW fuel cell in MATLAB/Simulink® and validated in different scenarios like dynamic variation in hydrogen pressure, stack temperature, load variation. The performance has been observed and compared with the conventional MPPT algorithms of Perturb and Observe (P&O) algorithm and Incremental Conductance (InC) algorithm. The proposed ANFIS-MPPT algorithm improves the power stability by 10–15% than the P&O and InC methods. Also, the proposed ANFIS-MPPT has 30% faster response as compared to the P&O algorithm, and 23% than the InC algorithm. From the analysis, it is observed that the ANFIS, P&O and InC methods are having the response time of 2.5 s, 3.6 s and 4.5 s respectively. Also the ANFIS method delivers the maximum power output of 1.26 kW, whereas the P&O and InC deliver 1.13 kW, 1.19 kW respectively. The detailed simulation analysis and results are presented in this paper.

Metadata schema for virtual building models in digital twins: VB schema implemented in GPT-based applications

A virtual building model (VBM) is a virtual entity that represents the physical behavior of a target building mathematically within a digital twin environment. The creation and synchronization of a VBM are achieved by utilizing various interrelated virtual sub-models, including behavior, correction, and distance models. To achieve continuous digital twinning, it is essential to manage the VBM with virtual sub-models. However, these metadata schemas have limitations in describing VBMs representing operational building behaviors within the concept of building digital twins (DTs). Therefore, this study proposes a novel metadata schema, termed the virtual building model metadata schema (VB schema), to represent and manage VBMs in DT-built environments. The VB schema is established according to the mathematical and semantic ontology of the in-situ modeling and calibration approach for constructing and correcting virtual models during building operations, and it is linked to physical entities, data, and applications within DTs. Specifically, it involves: (1) determining classes for operational data and virtual models; (2) establishing relationships for interactions between model and data entities, between model classes, between model and physical entities, and between model and applications; (3) defining properties for each class of models; and (4) extending into the exiting metadata schema of Brick. To demonstrate the proposed VB schema, a virtual model describing supply pressure behaviors in a central heating system was developed and represented using the VB schema for DT-enabled building operations. Additionally, the VB schema was utilized for implementing generative pre-trained transformer (GPT)-based DT applications, which highlights its benefits in enhancing ontology comprehension of DTs in the context of VBMs, improving autonomous problem-solving capabilities in real building systems, and providing better interpretation of application results compared to cases where only the Brick schema was used. The VB schema is expected to enable continuous and autonomous in-situ management of VBMs for intelligent building services within the DT.

Exploring nusselt number and friction factor correlations for sphere-shaped roughness elements on the absorber to enhance solar air heater efficiency

ABSTRACT This investigation is conducted to analyze the artificial surface roughness influence on the heat flow and friction characteristics within the ducts of solar air heaters (SAHs). This research aims to investigate the consequences of applying spherical-shaped surface roughness to the absorber in a linear and staggered manner with the intention of enhancing the heat transfer efficiency. The utilization of roughness elements in the shape of spheres is aimed at augmenting the heat transfer characteristics; however, it is crucial to acknowledge that this enhancement is concomitant with an elevation in pumping power due to heightened friction. An experimental campaign encom- passes a diverse set of operational and device parameters. These parameters include the Reynolds number (Re), which varies from 3,000 to 8,000. Additionally, the roughness pitch-to-height ratio (p/h) ranges from 10 to 20, while the roughness gap-to-height ratio (w/h) ranges from 4 to 8. Throughout the trials, a constant value of 0.06 is maintained for the roughness height-to-hydraulic diameter ratio (h/D) and an amount of 5 is maintained for the duct width-to-height ratio (W/H). The outcomes of this study indicate a considerable increase in the Nusselt number, ranging from 50.47% to 69.51%, concurrently with a substantial rise in the friction factor, ranging from 27.76% to 144.75%, when compared to designs using a smooth absorber surface in the context of SAHs. By utilizing the experimental data, relationships between the friction factor and the Nusselt number are established based on the artificial roughness parameters and the operating conditions. The current study’s findings significantly advance our knowledge of and ability to improve SAH systems’ heat transfer and friction characteristics. Thus, this investigation improves our understanding of these systems operational behavior in many situations.

MUSE: an open-access platform for urban expansion simulation with multitype patch generation engine and multilevel morphology regulation

Urban expansion models (UEMs) help unfold the mechanism, future pathways, and relevant repercussions of urban landscape dynamics. Although a plethora of UEMs have been developed, the field of open-access modeling platform for urban expansion simulation still presents gaps in terms of representing urban development events, regulating multilevel urban morphologies, and reflecting underlying regularities of physical urban growth. This study develops an open-access Multiengine Urban Expansion Simulation (MUSE) platform together with software that addresses some of these limitations. MUSE employs patch-based concepts and different patch generation engines to represent urban development events of distinctive types, enabling control over spatial morphology at landscape, class and patch levels. Moreover, MUSE incorporates two general regularities on urban development waves and urban diffusion and coalescence to govern physical urban expansion processes. Experiments in two cities examine MUSE’s ability in simulating realistic urban dynamics, and a series of synthetic experiments verify the operational behavior of the patch generation engines. These experiments show that MUSE can simulate a range of urban expansion types, including infill, edge growth and leapfrog expansion, and various morphologies, such as aggregated, sprawl, fragmented and compact. MUSE can empower practitioners to better project, analyze and understand complex urbanization dynamics.

Recovery of electrical power from exhaust air—role of vertical axis wind turbine

AbstractThis article explores the potential of regeneration of power from unnatural wind sources with the help of vertical axis wind turbines (VAWT). Researchers are searching for urban as well as industrial wind sources, which can be useful as the natural wind source to obtain electrical energy and utilize it. The wind sources considered here are the exhaust of the cooling or ventilation fans used in buildings, industries, and other places. The Darrieus VAWT extracts wind power from the exhaust air and reduces the power consumption of the concerned electrical drives. These uncommon energy sources have an inherent capability to recover a significant amount of energy without polluting the environment with less payback period. Recovered energy can be suitably converted into electrical energy and may be fed back to the power grid without any pollution, thus minimizing the total energy consumption of the building and reducing the cost operations. A detailed study of experimental models with different types of assembly and turbine models is conducted here with power outputs and operational behaviors on the existing systems. Various parameters and factors for existing and new applications are in detail that show the system has no negative impact on regular operation.

Exponential Sampling Type Kantorovich Max-Product Neural Network Operators

This article deals with the study of approximation behavior of the exponential sampling type Kantorovich max-product neural network operators based on sigmoidal activation function. We study point-wise and uniform convergence theorems in the space of continuous functions for these operators and determine the rate of convergence by means of logarithmic modulus of continuity. We also investigate the approximation of p -th ( 1 ≤ p < ∞ ) Lebesgue integrable functions by the aforementioned operators and study the rate of convergence exploiting Peetre’s K − functional.

Digital twins for electric propulsion technologies

As the space industry is undergoing an evolution, the current approaches toward design, development, and qualification of Electric Propulsion (EP) systems largely based on empirical “trial-and-error” methodologies are falling short of addressing the emerging needs and keeping abreast of the rapid changes in market trends. Furthermore, with the proliferation of Artificial Intelligence (AI) within the space industry toward next-generation autonomous satellites and spacecrafts, the conventional EP monitoring and control strategies become inadequate and need to give way to approaches compatible with satellite-level autonomy requirements. A digital twin (DT) – a technology capable of providing an accurate dynamically adapting virtual representation of a physical asset – is a game-changing concept that catalyzes the transcendence of the EP industry past its pressing challenges today. In this paper, we aim to: (i) define the DT concept, highlighting how it surpasses traditional modelling, (ii) enumerate the DT’s breakthrough promises for the EP industry, and (iii) specify the challenges to realize practical and scalable EP DTs. Additionally, we report on the technical progress achieved and/or planned at Imperial Plasma Propulsion Laboratory to fill the foundational gaps in three building block elements of DTs, namely, (i) a cost-effective kinetic model to generate extensive high-fidelity databases for machine learning (ML), (ii) ML-enabled models for prediction and analysis of performance and operational behavior, and (iii) a DT architecture that integrates the numerical models in terms of a computing infrastructure and provides data pipelines and interfaces for the DT’s data exchanges with the real world, its dynamic updating, and uncertainty quantification.

Comparison of passive and manual chlorination in small piped water networks in rural Ghana: Technical performance, ease-of-use, and cost

Chlorination is the most common water treatment method globally and leads to proven health benefits. Yet, many rural water supplies in low-income settings are unchlorinated, exposing consumers to waterborne diseases. Insufficient technical and financial capacity of water suppliers in low-resource settings are common barriers to more widespread chlorination. We conducted a case study of two approaches to chlorinate small piped water supplies− passive (inline) chlorination and manual chlorination− and compared their technical performance, ease-of-use, and costs in rural Ghana. Based on 685 water quality measurements across two piped networks over three months, both methods provided adequate free chlorine residuals (i.e., 0.2–2.0 mg/L) most of the time (71% for manual chlorination and 86% for passive chlorination). Follow-up measurements five months later revealed a decline in chlorine levels with the manual approach (47% in the target range) and an increase with the passive (inline) approach (100% in the target range). We observed large fluctuations in chlorine levels over time, particularly with inline chlorination, that pH, temperature, conductivity, and turbidity variations did not fully explain. Temporal changes in chlorine demand and/or inconsistently implemented protocols possibly contributed to these fluctuations. Inline chlorination scored higher for ease-of-use (85%) than manual chlorination (70%) but was less financially viable: it represented an 11% increase in operational expenses, compared to 4% for manual chlorination. Initial equipment and installation cost approximately 6,000 USD for inline chlorination and about 260 USD for manual chlorination. Our results highlight the tradeoffs between passive (inline) and manual chlorination. Although less favorable for ease-of-use, manual chlorination is more viable financially and can achieve comparable performance with strict dosing protocol adherence, suggesting this approach deserves similar consideration as passive chlorination when evaluating options for low-resource settings. Both methods are susceptible to changes in operator behaviors and require external oversight plus support for troubleshooting and recalibration.

Simulation of Coherent Excavator Operations in Earthmoving Tasks Based on Reinforcement Learning

Earthwork operations are critical to construction projects, with their safety and efficiency influenced by factors such as operator skill and working hours. Pre-construction simulation of these operations is essential for optimizing outcomes, providing key training for operators and improving safety awareness and operational efficiency. This study introduces a hierarchical cumulative reward mechanism that decomposes complex operational behaviors into simple, fundamental actions. The mechanism prioritizes reward function design elements, including order, size, and form, thus simplifying excavator operation simulation using reinforcement learning (RL) and enhancing policy network reusability. A 3D model of a hydraulic excavator was constructed with six degrees of freedom—comprising the boom, arm, bucket, base, and left/right tracks. The Proximal Policy Optimization (PPO) algorithm was applied to train four basic behaviors: scraping, digging, throwing, and turning back. Motion simulation was successfully achieved using diggable terrain resources. Results demonstrate that the simulated excavator, powered by RL neural networks, can perform coordinated actions and maintain smooth operational performance. This research offers practical implications by rapidly illustrating the full operational process before construction, delivering immersive movies, and enhancing worker safety and operational efficiency.

Exploration of drag on the thin film of micropolar fluid flow within a permeable medium

Advances in thin film acquired many industrial applications because of their use in several products like electronic devices, magnetic recording media, LED, optical coating, etc. Additionally, thin film has an extensive role in the study of multiferroic materials and superlattices in quantum phenomena. Therefore, it is an urge to predict the importance of drag employing Darcy-Forchheimer on the thin film flow of micropolar liquid through an expanding plate embedding with a permeable medium. Moreover, the current model enriches by incorporating the impact of Soret because of the cross-diffusion process and the radiative heat. By using the appropriate transformed variables, the designed problem is distorted, and further, these sets of equations are handled numerically employing Runge-Kutta shooting technique. The computation is carried out by deploying in-house built-in function bvp4c in MATLAB. The significant operational behavior of the manipulated quantities is accessible graphically and deliberated in the discussion section. The important findings are elaborated as; the angular velocity distribution shows a greater deceleration for the increasing microrotation and the inertial drag effect. Further, the thermo-diffusion due to Soret also attenuates the concentration profile and the solutal thickness became thinner for the higher heavier species.

Performance of advanced ceramic round tools when turning Inconel 718

Nickel-based superalloys, like Inconel 718, are very attractive metals for aerospace applications due to their excellent mechanical properties and thermal stability. However, these materials pose a significant challenge to the metal machining industry due to their very low machinability, especially in terms of reduced tool life because of the high heat generated during cutting. Nevertheless, it can be improved using high-performing tools that retain their hardness when exposed to high temperatures, such as ceramic tools. In this context, the study aims to compare the performance of two advanced ceramic tools, namely an alumina ceramic tool reinforced with SiC whiskers and a Bidemics™ one, when turning Inconel 718 at different cutting speeds, using as a baseline a conventional coated cemented carbide tool. First, the three inserts were characterized in terms of topography, thermal conductivity, and hot hardness to fully understand their operational behavior. Then, turning trials were conducted showing that both the ceramic tools outperform the coated carbide one in terms of tool life, with Bidemics™ demonstrating the best performance among all. This can be ascribed to its very high hardness maintained even at high temperatures, as well as its moderate thermal conductivity.

ADRC-Based cooperative control for unmanned towing operation by multiple DP tugboats: A comparative study of two cooperative controllers

This paper addresses the challenge of coordinated manipulation of an unactuated floating object by multiple tugboats to execute both positioning and towing operation within complex marine environments. We proposes a multi-layer cooperative control algorithm for the multi-tugboat system, including tugboat control level and cooperative control level. At the individual tugboat control level, the dynamic positioning system (DPS) has been enhanced to match the operational behavior of the tugboat, enabling it to handle cable tension and environmental disturbances during transit. The controller incorporates a simple yet effective linear active disturbance rejection control method (ADRC) to counter external disturbances and ensure accurate trajectory tracking without relying on preset models. Moving to the multi-tugboat collaboration level, two distinct control strategies are proposed for towing operations: formation-based (FB) and force-allocation-based (FAB). The FB strategy involves multiple tugboats forming a coordinated formation, with control focused on the formation center to indirectly manipulate the object. On the other hand, the FAB strategy utilizes model predictive control (MPC) for the object to allocate the necessary towing force for each cable, thereby determining the required actions for each tugboat based on the cable model and the needed towing force. Simulation results demonstrate that both control strategies can effectively maneuver the floating object with high accuracy to perform positioning and towing tasks. Nevertheless, due to the variations in their fundamental mechanisms, there are significant discrepancies in towline tension, tugboat utilization, and energy consumption.

Integration of the exploding foil initiator with capacitor discharge unit and its performance characterization

This study presents a novel integrated exploding foil initiator system (EFIs), consisting of a planar switch, an EFI chip, and a capacitor. Additionally, we propose an evaluation method for integrated EFIs that combines numerical simulations with experimental testing, enabling a thorough assessment of their performance. Under test conditions of 900 V/0.22 μF, the EFI demonstrated an inductance of 10.2 nH and a resistance of 107.5 mΩ, measured via the sampling resistance method. The operational behavior of the EFIs was analyzed through a two-dimensional metal electrical explosion model and a one-dimensional flyer propulsion model, with the results compared to experimental data. Results indicated that under 900–1200 V/0.22 μF, the deviations between measured and calculated values for electrical explosion performance and flyer velocity were both within 5 %, validating the accuracy of the evaluation approach. Firing tests further confirmed that the EFIs successfully detonated HNS-IV at 1000 V/0.22 μF.

A vine-copulas based multi-sensor fusion structural damage monitoring method and its application in dam engineering

As a civil engineer that is susceptible to the mechanism of slow and continuous deterioration, the dam must detect damage according to the static data of the arranged sensors, which is an important issue in structural health monitoring. Due to the characteristics of huge solid structures, damage with a slight degree and small range usually does not cause significant changes in the monitoring data of a single sensor. Therefore, it is difficult to effectively detect local damage by traditional monitoring methods that establish operating warning values for a single sensor. Currently, there have been some approaches to fuse sensor information that consider correlations between multiple sensors as well as the overall operational behavior of the dam. However, their objectives are focused on improving the accuracy of response variable prediction models without addressing the local damage identification aspect. In this study, we apply the Vine-Copula model for the first time in a multi-sensor information fusion dam damage detection method based on static monitoring data. In this way, it improves the sensitivity of local damage identification for huge solid structures. A prediction model is fitted with the measuring data of each sensor to obtain the residual series. Then the joint probability distribution of the multidimensional residuals is acquired by constructing the Vine-Copula model. Finally, the joint cumulative distribution function value is used as an alarm limit to determine whether the structure has an abnormal damage condition. The effectiveness and accuracy of the proposed method were demonstrated in both a numerical arch dam simulating local damage and an actual rockfill dam engineering with cracks at the crest.