Operational Limits Research Articles

Microscopic Analysis and Evaluation of Thermal Elevation and Wear of Drills for Implant Site Preparation: An In Vitro Study

Drilling for implant site preparation generates heat, which can cause bone necrosis if temperatures exceed 47 °C for over a minute. Factors influencing heat include drill size, speed, pressure, irrigation, and tool wear. Frequent drill replacement is essential, as wear from repeated use and sterilization affects performance. This study compared three pilot drills with similar designs from different manufacturers, testing each on pig ribs for 15 perforations after 15 sterilization cycles. Researchers measured temperature increase, drilling time, and surface wear. Results showed that drill no. 1 generated more heat than drills no. 2 and no. 3, though none reached critical temperatures. Drill no. 2 took the longest to reach the desired depth and displayed the most deformation. Findings highlight the importance of adhering to the recommended operational limits, suggesting that drills should be replaced after 15 cycles to ensure efficacy and patient safety.

A Multi-Objective Energy Optimization Model for Renewable Energy Systems with Hybrid Energy Storage

Building a Renewable Energy System (RES) is a viable way to address resource depletion and accomplish decarbonization. This study presents a hybrid power system that combines wind, solar, battery, and thermal energy storage. It also examines the co-optimization of scheduling and operation for multiple objectives. The hybrid system combines the affordability of thermal energy storage (TES) with the adaptability of batteries to effectively address the issue of intermittent RES. A new approach for integrated operation is offered, which relies on the electrical block's operation limit. The planning-operation co-optimization system considers minimizing the Net Present Cost (NPC) and reducing power supply likelihood todetermine the best operation limit and sizing decision factors. The co-optimization issue is addressed using novel multi-objective decision-making (MO-DM). This approach incorporates the Decision-Maker (DM) preferences data to direct the evolutionary process toward the desired area. In addition, a data-driven prediction model captures the risks and losses associated with wind generation. The case study's findings indicate the following: (1) The data-driven system has a higher level of precision in wind power projection when compared with commonly used physical simulations. (2) The suggested MO-DM exhibits superior integration, variety, and robustness achievement in the DMchosen area compared to others. (3) The combined battery-thermal energy storing structure achieves improved economy and dependability through the optimum organized operation approach, in contrast to using a single energy storage system under various testing constraints.

STRESS ANALYSIS OF THE MAIN COMPONENTS OF IMPROVED GATE VALVE CONSTRUCTION

This study explores the stress resistance of an improved valve design under high-pressure conditions, focusing on stress distribution across both the sealing element and the valve body. A 2D model of the valve was created in AutoCAD and analyzed using Python’s Matplotlib, simulating performance under pressures up to 75 MPa, 5 MPa above the operational limit. Results reveal critical stress patterns, with stress concentrations reaching up to 325 MPa along the inner radius of the sealing element and valve body. Radial, longitudinal, and circumferential stresses were evaluated, showing a gradual decrease in compressive forces from the inner to outer surfaces. The contact areas between the sealing element and valve body emerged as critical zones, with high-pressure exposure raising the risk of early material fatigue and functional degradation. Overall, the improved valve design exhibits significant resilience under high-pressure conditions. However, sustaining this performance over time will require proactive inspection and maintenance to prevent premature wear and material fatigue. This research provides valuable insights for enhancing valve designs and improving durability in high-pressure applications within the oil and gas industry. The analysis demonstrates that the improved valve design can withstand high pressures effectively, but highlights the importance of routine inspection and maintenance to prevent premature failure due to material fatigue. Continuous monitoring, particularly around the inner radius and critical contact areas, is recommended to ensure operational longevity and reliability under fluctuating pressure conditions. Keywords: Linear motion valve, body, finite element analysis, wear, seal.

Model-predictive fault-tolerant control of safety-critical processes based on dynamic safe set

Industrial systems and chemical plants heavily rely on automation and control systems for seamless operations. However, the susceptibility of these systems to various faults poses threats to processes, leading to economic losses and safety risks. Here, a robust fault-tolerant control (FTC) strategy is developed that can take proactive measures during faults involving in-time activation of a backup controller, to ensure that the system remains within safe operational limits. It is based on the Dynamic Safe Set (DSS) which is the set of initial process states that meet safety constraints at all times, and the dynamic safety margin (DSM) which is the minimum distance from the DSS boundary. For just-in-time corrective action, a critical fault function is introduced, defined as the time required by the system to cross the DSS boundary under the nominal controller only. This critical fault function is calculated offline and is integrated with a real-time fault size estimation to formulate the controller reconfiguration logic to keep system within DSS. A linear functional observer is used to estimate fault size, combined with a predictive scheme, to enhance robustness during the transient period of fault estimation. This configuration avoids unnecessary control actions while ensuring timely intervention. The proposed FTC strategy is tested on an exothermic Continuous Stirred Tank Reactor (CSTR) case study. The results demonstrate the strategy's effectiveness in handling process faults, ensuring both stability and safety constraints are met. Thus, this paper contributes to the advancement of FTC ensuring the resilience of industrial systems in the face of unforeseen challenges.

Offshore wind project installations: an advanced approach for weather risk assessments

Abstract This paper presents the development of a sequence-based simulation tool for the weather risk assessment of offshore work processes. The approach developed at the Fraunhofer Institute for Wind Energy Systems is the Advanced Weather Time Series Scheduling (Ad-WATSS) method. For statistical significance, this method combines hindcast weather time series of many years with the weather restrictions associated with offshore activities. The method is incorporated into the software tool COAST, where a project plan schedule is simulated by placing activities according to their operational limits, constraints and relationships, and minimum-required time for each operation. A scenario of an offshore wind installation project in the North Sea is used as reference test case for a weather risk assessment using the developed tool and ERA5 weather data. The assessment is then compared with the weather window statistics approach, based on the same weather data sets. The results from both approaches are analysed and compared on a project and task level detail. The results from the sequence-based simulations show that the method is able to capture the long-term variability and extreme events in weather conditions, making it a reliable tool for the simplification of the weather data-based planning, validation, and assessment of offshore projects.

High-count-rate particle tracking in proton and carbon radiotherapy with Timepix2 operated in ultra-short acquisition time

This work investigates the operational acquisition time limits of Timepix3 and Timepix2 detectors operated in frame mode for high-count rate of high deposited energy transfer particles. Measurements were performed using alpha particles from a 241Am laboratory source and proton and carbon ion beams from a synchrotron accelerator. The particle count rate upper limit is determined by overlapping per-pixel particle signals, identifiable by the hits per pixel counter > 2, indicating the need to decrease acquisition time. On the other hand, the lower limit is the time required to collect the particle deposited charge while maintaining spectral properties. Different acquisition times were evaluated for an AdvaPIX Timepix3 detector (500 μm Silicon sensor) with standard per-pixelDigital to Analog Converter (DAC)settings and a Minipix Timepix2 detector (300 μm Silicon sensor) with standard and customized settings the pulse shaping parameter and threshold. For AdvaPIX Timepix3, spectra remained accurate down to 100 μs frame acquisition time; at 10 μs, loss of collected charge occurred, suggesting either avoiding this acquisition time or applying a correction. Timepix2 allowed acquisition times down to 100 ns for single particle track measurements even for high energy loss, enabled by a new Timepix2 feature delaying shutter closure until full particle charge collection. This work represents the first measurement utilizing Timepix-chips pixel detectors in an accelerator beam of clinical energy and intensity without the need to decrease the beam current. This is made possible by exploiting the short shutter feature in Timepix2 and a customized per-pixel energy calibration of the Timepix2 detector with a larger discharging signal value which allowed for shorterTime-over-Threshold (ToT)signal. These customized settings extend the operation of the pixel detectors to higher event rates up to 109 particles/cm2/s.

Impact of Driving Timing and Road Types on the Operating Regions of Electric Two-wheeler Powertrain Components under Indian Road Conditions

Among the different classes of electric vehicles (EVs), electric two-wheelers (E2Ws) are securing more enticement towards the commutator for regular usage due to their higher suitability in the heterogeneous traffic conditions of India. However, the driving range of the E2Ws is the major concern in increasing its penetration rate in road transportation. To eradicate the range anxiety of commutators by redesigning the current E2W powertrain configuration, this study strives to insights into the operational limits of powertrain elements such as the battery and motor in E2W under multiple operational circumstances such as driving style, pavement, and ambient conditions. Regarding this, the E2W with data acquisition system (DAC) connected with an onboard diagnosis (OBD) port is utilized to acquire the data related to powertrain components and vehicles for four driving trips (trips 1–4) under three major road segments (Rural, expressway, and urban) of India. The operating and computed performance metrics, comprising battery voltage and current, state-of-charge (SOC), energy consumption, motor current, speed, efficiency, and so on, are then compared throughout driving trips and road segments. The mean velocity of E2W for trips 1 to 4 is 31.91, 33.68, 39.03, and 35.58 km/h, respectively. The results disclosed that total energy consumption and energy consumption per km. are higher during trip 3 due to higher average vehicle speed. Also, it has a higher depth-of-discharge (DOD) of 83.91 % than other driving trips. Further, a higher rate of SOC drop, energy consumption and battery temperature rise are found at highway road segments.

Region-Based Approach for Machining Time Improvement in Robot Surface Finishing

Traditionally, in robotic surface finishing, the entire workpiece is processed at a uniform speed, predetermined by the operator, which does not account for variations in the machinability across different regions of the workpiece. This conventional approach often leads to inefficiencies, especially given the diverse geometrical characteristics of workpieces that could potentially allow for different machining speeds. Our study introduces a region-based approach, which improves surface finishing machining time by allowing variable speeds and directions tailored to each region’s specific characteristics. This method leverages a task-oriented strategy integrating robot kinematics and workpiece surface geometry, subdivided by the clustering algorithm. Subsequently, methods for optimization algorithms were developed to calculate each region’s optimal machining speeds and directions. The efficacy of this approach was validated through numerical results on two distinct workpieces, demonstrating significant improvements in machining times. The region-based approach yielded up to a 37% reduction in machining time compared to traditional single-direction machining. Further enhancements were achieved by optimizing the workpiece positioning, which, in our case, added up to an additional 16% improvement from the initial position. Validation processes were conducted to ensure the collaborative robot’s joint velocities remained within safe operational limits while executing the region-based surface finishing strategy.

Pipelined information flow in molecular mechanical circuits leads to increased error and irreversibility

Pipelining is a design technique for logical circuits that allows for higher throughput than circuits in which multiple computations are fed through the system one after the other. It allows for much faster computation than architectures in which inputs must pass through every layer of the circuit before the next computation can begin (phased chaining). We explore the hypothesis that these advantages may be offset by a higher error rate, logical irreversibility, and greater thermodynamic costs by simulating pipelined molecular mechanical circuits using an explicit physical model. We observe the emergent logical irreversibility, and see that the simultaneous action of multiple components indeed leads to a higher error rate than in phase-chained circuits. The thermodynamic costs of operating the gates are much larger than in equivalent phase-chained circuits, and these costs do not appear to tend to zero in the limit of slowgate operation. Redesigning the gates to eliminate errors and artificially enforcing logical reversibility reduces the thermodynamic costs and recovers thermodynamically reversible behavior in the limit of slow gate operation. The breakdown of logical reversibility and accuracy are both associated with a breakdown of the digital behavior of the device, likely contributing to thermodynamic costs that are large relative to the scale of the information being processed. Published by the American Physical Society 2024

RF coil design strategies for improving SNR at the ultrahigh magnetic field of 10.5T.

Toward pushing the boundaries of ultrahigh fields for human brain imaging, we wish to evaluate experimentally achievable SNR relative to ultimate intrinsic SNR (uiSNR) at 10.5T, develop design strategies toward approaching the latter, quantify magnetic field-dependent SNR gains, and demonstrate the feasibility of whole-brain, high-resolution human brain imaging at this uniquely high field strength. A dual row 16-channel self-decoupled transmit (Tx) and receive (Rx) array was developed for 10.5T using custom Tx/Rx switches. A 64-channel receive-only array was built to fit into the 16-channel Tx/Rx array. Electromagnetic modeling and experiments were used to define safe operational power limits. Experimental SNR was evaluated relative to uiSNR at 10.5T and 7T. The 64-channel Rx array alone captured approximately 50% of the central uiSNR at 10.5T, while an identical array developed for 7T captured about 76% of uiSNR at 7T. The 16-channel Tx/80-channel Rx configuration brought the fraction of uiSNR captured at 10.5T to levels comparable to the 64-channel Rx array at 7T. SNR data displayed an approximate dependence over a large central region when evaluated in the context of uiSNR. Whole-brain, high-resolution -weighted and T1-weighted anatomical and gradient-recalled-echo BOLD-EPI functional MRI images were obtained at 10.5T for the first time with such an advanced array. We demonstrated the ability to approach the uiSNR at 10.5T over the human brain, achieving large SNR gains over 7T, currently the most commonly used ultrahigh-field platform. Whole-brain, high-resolution anatomical and EPI-based functional MRI data were obtained at 10.5T, illustrating the promise of greater than 10T fields in studying the human brain.

Investigation of Ammonia/Hydrogen Mixtures and Pilot-Split Strategies in a Laboratory-Scale Radial Swirl Combustor

Abstract The transition to a decarbonized energy future relies on identifying the most suitable alternative fuels that can meet the needs of various energy sectors. While both ammonia and hydrogen are zero-carbon energy vectors, their physical properties and burning characteristics sit on either side of that of natural gas. Hence, mixtures of ammonia and hydrogen are being increasingly looked at as having the potential to fuel current energy systems without requiring significant combustor redesign. However, the combustion characteristics and operation limits for different ammonia/hydrogen mixtures still need to be evaluated. For gas turbine applications in particular, the effect of ammonia/hydrogen mixture composition and operating condition on flame behavior and stability is not well understood. The current work was carried out in a laboratory scale, radial swirl-stabilized turbulent combustor. A systematic study of two ammonia/hydrogen blend ratios (70:30 and 80:20 by volume) and a range of equivalence ratios were tested for different pilot-split ratios, to understand the effect on flame shape, stability and dynamics. Time-resolved pressure and integrated heat release fluctuations were measured to evaluate combustor dynamics, and NH2* chemiluminescence flame images were captured to understand spatial differences in flame structure. When comparing blend ratios, differences were observed in flame macrostructures and combustor dynamics, which could be largely attributed to the considerable difference in the laminar flame speeds of the blends. The addition of pilot generally improved the stability and lean operation for both blend ratios.

Grain Structure Engineering in Screen-Printed Silver Flake-Based Inks for High-Temperature Printed Electronics Applications.

We extensively studied serigraphic screen-printed commercial silver flake inks loaded with silicon inclusions in order to achieve pinning at the grain boundaries. Based on grain size measurements using electron backscattered diffraction (EBSD), commercial silver ink with silicon microparticle content of 5 wt.% shows significant grain growth retardation compared to pristine silver ink, which stabilizes electrical conductivity up to 700 °C via a Zener pinning mechanism. The modified silicon-loaded silver ink experiences a two-times increase in grain size when heated up to 700 °C, compared to a seven-times increase for pristine silver ink. In turn, this enables operation temperatures significantly higher than the conventional operational window of microparticle-based silver inks, which are usually limited to 400 °C. Using isothermal exposures of 10 min up to 4 h, this phenomenon is observed at temperatures ranging from 250 °C to 900 °C. The electrical conductivity stability, grain size evolution and oxide contents were studied up to 4 h. The activation energy of silver ink with silicon inclusions is 54% lower than for pristine silver ink due to the pining effect, which retards grain growth via the Zener mechanism. Most importantly, the electrical resistivity remains stable up to 700 °C, which is more than twice the operation limit for off-the-shelf screen-printable silver flake inks. Hence, we demonstrate that adding controlled amounts of silicon particles to silver inks for grain structure engineering can open new vistas of possibilities for screen-printed metallic inks.

Reverse characterization prediction of diamond Schottky barrier power devices using machine learning: Predicting breakdown voltage and Baliga figure of merit

Diamond power devices showed great potential for high-performance and low-loss applications at high frequencies. Schottky power diodes on the diamond have markedly higher threshold reverse operation limits than other power devices, yet they are still far from the ideal limit. Therefore, utilizing the device capabilities across optimizing device parameters is severely time- and resource-intensive considering traditional trial-and-error experimental methodology. On the other hand, data-driven techniques can accelerate device optimization and reduce resource consumption. This work demonstrates machine learning models that predict breakdown voltage in addition to Baliga's power figure of merit (BFOM) for the first time. An experimentally driven dataset is constructed because of its reliability, precision, and potential for generalization. This dataset contains current-voltage characteristics raw data for more than 400 devices fabricated on heteroepitaxial diamond. Four machine learning algorithms are explored and evaluated based on 5-fold cross-validation to prevent overfitting. The extra-tree model shows the highest performance that accurately predicts the breakdown voltage, and the BFOM with R2 equal to 0.924 and 0.911, respectively. Additionally, it showed robust prediction accuracy on unseen data with an 8 % average relative error of 16 devices. Achieving this high accuracy indicates the potential of these models for generalization on various datasets.

On Microplasticity-induced Fatigue Fracture and its Relation to Entropy

Abstract The study delves into the intricate effects of microplasticity on fracture formation in testing specimens under axial cyclic loading. The primary aim is to pinpoint the juncture at which microplasticity becomes discernible across the stress cycle. Fatigue tests are conducted on varied specimens until failure using a fatigue testing machine, while recording parameters such as frequency, stress amplitude, applied power, and tensile strain. The investigation seeks to ascertain whether cracks must attain a specific size before manifesting these subtle alterations. A conjectured relationship is proposed between the number of cycles and entropy throughout the process. Additionally, a hypothesis is posited suggesting that microplasticity emerges only once the crack surpasses a certain threshold, such as grain size. This research provides insights into material fracture mechanisms and their implications for product durability and safety. Such discernments into the product life cycle under analogous conditions hold promise for delineating operational limits.

Ship-based RPA operations for cetacean research in Antarctica: progress, opportunities and challenges

Data collection facilitated by remotely piloted aircraft (RPA) has proven to be revolutionary in many disciplines including for research in extreme environments. Here we assess current use and utility of small multirotor remotely piloted aircraft (RPAs) for the challenging role of facilitating ship-based cetacean research in Antarctica. While such aircraft are now used routinely in sheltered environments in and off Antarctica, a comprehensive literature review found that RPA-mediated cetacean research conducted from ships at sea and outside of the Antarctic Peninsula region was relatively uncommon. In order to determine the potential utility of ship-based multirotor RPA operations for cetacean research, we repeatedly deployed small RPAs during a multidisciplinary research voyage in maritime East Antarctica to collect scientific data contributing to an understanding of krill and krill predator interactions. RPA flight metrics (duration, height, length, speed, distance from ship, battery drainage, satellites acquired) were compared to ship underway environmental sampling data. At a mean duration of 12 minutes, these 139 RPA flights were relatively short yet adequate to achieve the science intended, namely a range of cetacean related data streams including photogrammetry, photo identification, behavioural observations and whale blow sampling in addition to water sampling and collection of general scenic imagery. RPA flight operations were constrained by wind speed but not by air temperature with flights undertaken throughout the full range of air temperatures experienced (down to –9.5°C) but not throughout the full range of wind speeds experienced. For a 12-minute flight duration, battery drainage was around 60% indicating that the RPAs were rarely pushed to their operational limit. There was little evidence that the cold impacted RPA lithium battery performance with estimated maximum flight time within approximately 10% of expected flight time for the RPA platforms most used. Whist small multirotor RPAs are rarely applied to cetacean related research in maritime East Antarctica, we demonstrate their value and potential to deliver data critical to address knowledge gaps that challenge the effective management of both krill and their predators.

Benign Saturation of Ideal Ballooning Instability in a High-Performance Stellarator.

To examine the robustness of the designed 5% β limit for high-performance operation in the W7-X stellarator, we undertake nonlinear magnetohydrodynamic (MHD) simulations of pressure-driven instabilities using the m3d-c1 code. Consistent with linear analyses, ideal ballooning instabilities occur as β exceeds 5% in the standard configuration. Nonetheless, the modes saturate nonlinearly at relatively low levels without triggering large-scale crashes, even though confinement degradation worsens as β increases. In contrast, in an alternative configuration with nearly zero magnetic shear, ideal interchange modes induce a pressure crash at β=1%. These results suggest that the standard W7-X configuration might have a soft β limit that is fairly immune to major MHD events, which enhances the appeal of the stellarator approach to steady-state fusion reactors.

Operating Limits and Control Variables in Photovoltaic Solar Plants with a Net Effective Capacity of 5 MW Connected to the SIN in Colombia

Operating Limits and Control Variables in Photovoltaic Solar Plants with a Net Effective Capacity of 5 MW Connected to the SIN in Colombia

A Virtual Reality Gearbox Experiment Platform Based on Hand Tracking and Natural Language Processing

In manufacturing engineering education, the gearbox is an essential mechanical component and a fundamental skill students must master. Recent data suggests that insufficient understanding of its load capacity and exceeding operational limits can damage internal components, potentially leading to severe consequences like fires. In order to address the challenges faced by physical laboratories and existing traditional virtual labs in the new engineering disciplines, including the lack of insufficient experimental safety, operational real-ism, insufficient personalized learning support, and the difficulty in creating immersive learning environments, we introduce a Virtual Reality Gearbox Experiment Platform Based on Hand Tracking and Natural Language Processing (VRGEPHTNLP). This platform aims to enhance the realism of detailed interactions, provide personalized learning experiences, and create immersive environments, thereby improving students' learning efficiency and practical skills. In order to enhance the teaching of gearboxes, we have developed the VRGEPHTNLP by integrating hand-tracking technology, the GPT3.5 large language model (GPT3.5 LLM), and Azure technology. This application allows for comprehensive observation and assembly-disassembly teaching functionalities of parts. We offer an interaction experience rich in detail and environmental immersion, alongside personalized feed-back and guidance in response to student inquiries. Compared to traditional computer-based virtual labs and conventional VR laboratories, our VRGEP-HTNLP exhibits significant advantages in improving user interaction realism, enhancing personalized learning support, and optimizing the immersion of the learning environment.

Transmission coefficient and probability of intersubband transitions in [formula omitted] superlattices: Effect of non-parabolicity

Our study investigates optical transition energies in GaAs/AlGaAs quantum multiwell infrared photodetectors. These devices exploit transitions within subbands, necessitating accurate theoretical predictions to optimize their performance. We first determine the energetic positions of conduction minibands and investigate how band non-parabolicity influences the width of these minibands. Furthermore, we analyze the impact of non-parabolicity on transition probabilities within the quantum wells. Additionally, our study explores the transmission coefficient, which exhibits a decrease with increasing barrier height. This phenomenon affects electron transmission efficiency and is associated with quantum reflection processes. Higher barrier heights require greater energy for electrons to traverse, influencing device functionality. Understanding these factors is crucial for advancing the design and performance of GaAs/AlGaAs quantum multiwell photodetectors, offering insights into their operational limits and potential optimizations.

Control barrier function based visual servoing for Mobile Manipulator Systems under functional limitations

This paper proposes a new control strategy for Mobile Manipulator Systems (MMSs) that integrates image-based visual servoing (IBVS) to address operational limitations and safety constraints. The proposed approach based on the concept of control barrier functions (CBFs), provides a solution to address various operational challenges including visibility constraints, manipulator joint limits, predefined system velocity bounds, and system dynamic uncertainties. The proposed control strategy is a two-tiered structure, wherein the first level, a CBF-IBVS controller calculates control commands, taking into account the Field of View (FoV) constraints. By leveraging null space techniques, these commands are transposed to the joint-level configuration of the MMS, while considering system operational limits. Subsequently, in the second level, a CBF velocity controller employed for the entire MMS undertakes the tracking of the commands at the joint level, ensuring compliance with the predefined system’s velocity limitations as well as the safety of the whole combined system dynamics. The proposed control strategy offers superior transient and steady-state responses and heightened resilience to disturbances and modeling uncertainties. Furthermore, due to its low computational complexity, it can be easily implemented on an onboard computing system, facilitating real-time operation. The proposed strategy’s effectiveness is illustrated via simulation outcomes, which reveal enhanced performance and system safety compared to conventional IBVS methods. The results indicate that the proposed approach is effective in addressing the challenging operational limitations and safety constraints of mobile manipulator systems, making it suitable for practical applications.