Nominal Point Research Articles

Innovative fuzzy logic type 3 controller for transient and maximum power point tracking in hydrogen fuel cells

This study introduces an advanced Fuzzy Logic Type 3 (FLT3) controller for Proton Exchange Membrane Fuel Cells (PEMFCs), aiming to optimize Maximum Power Point Tracking (MPPT) under dynamically varying temperature conditions. The FLT3 controller advances fuzzy logic control by incorporating an additional layer of uncertainty modelling, which enhances its ability to manage the inherent nonlinearities in PEMFC systems, such as temperature fluctuations and gas pressure variations. The controller is developed and validated through MATLAB/Simulink simulations, using a refined rule based on mechanism with finely tuned membership functions for precise adaptation to changing conditions. When compared to traditional Perturb and Observe (P&O) and Fuzzy Logic Type 2 (FLT2) controllers, the FLT3 controller demonstrates superior performance by achieving faster sitting times, minimizing power fluctuations, and maintaining operation closer to the nominal power point, particularly under transient conditions for hydrogen-based fuel cell. This innovative approach significantly improves the efficiency and stability of PEMFC systems, marking a substantial advancement in their operational management.

Transient Analysis of Flow Unsteadiness And Machine Instabilities In a Centrifugal Compressor at Surge and Second Quadrant Operation

Abstract Instabilities in turbomachinery operation originate from intrinsic flow unsteadiness, sudden variations of operating conditions, and interactions with the surrounding system, affecting both system stability and machine reliability. The flow unsteadiness, presenting a characteristic behaviour, requires a deep understanding of the underlying flow fundamentals, a careful analysis using advanced experimental methods and a clear distinction on how the system might lead to instabilities. The identified approach addresses deep surge and second quadrant characterization. The analysis presented here benefits from the responsiveness and flexibility of the experimental test rig, fine tuning of the system layout, the instrumentation installation, and the transient tests procedure. The main focus area is the time-frequency analysis of flow and pressure signals at transients, thus providing a proper reconstruction of flow mechanisms and instability evolution. Valuable techniques include: short-time fast Fourier transform, wavelet analysis, and Wigner-Ville distribution; coherence between flow and pressure, to trace waves propagation, is considered too. These, presented outlining their strengths and weaknesses, are evaluated considering real time field applicability with regards to computational resources too. The experimental campaigns and data processing are presented, with a test matrix covering a wide range of parameters, including system layout and surge volume size, rotational speeds, flow rates ranging from nominal point to full second quadrant operation. These data are vital for system modeling validation for a full compressor-system digital twin. Results indicate the importance of ensuring reliable data acquisition and analysis, with adequate instrumentation range, accuracy, synchronization, responsiveness and positioning.

Ad Hoc Modeling of Rate-Dependent Adhesion in Indentation Relaxation Testing.

The phenomenon of rate-dependent adhesion has long been recognized as an intricate problem, and the so-far-developed physics and mechanics-based approaches resulted in analytical relations between the implicit form between the work of adhesion and the contact front velocity which are difficult to implement in practice. To address this issue in the framework of spherical indentation, the adhesion relaxation test in a nominal point contact is introduced to estimate the rate-dependent adhesion. Based on a stretched exponent approximation for the contact radius evolution with time, a relatively simple four-parameter model is proposed for the functional relation between the work of adhesion and the contact front velocity, and its fitting performance is compared to that of the known Greenwood-Johnson and Persson-Brener models.

Optimization of Component Assembly in Automotive Industry

Abstract This article is devoted to the positioning of glued parts by robots in the process of manufacturing automotive headlights, with the possibility of generalization to the mutual positioning of any 3D object. The authors focused on the description of the mathematical method that leads to the optimization of the robot arm setting and ensures the closest contact of the glued parts. The contact surfaces of the two joined parts are, in the ideal case, identical in shape and their optimal alignment is considered to best align the position of the nominal points on the base part with the position of the control (measured) points on the part manipulated by the robot.

Reflection of a rightward-moving oblique shock of first family over a steady oblique shock wave

The reflection of a rightward-moving oblique shock (RMOS) belonging to the first family, over an initially steady oblique shock wave (SOSW) produced by a wedge, is studied in this paper. To cover all possibilities, the problem is divided into a pre-shock reflection problem, for which the incident shock is assumed to reflect over the pre-interaction part of the SOSW, and a post-shock reflection problem, for which the incident shock is assumed to reflect over the post-interaction part. Such division, together with the definition of the equivalent problem defined on the reference frame co-moving with the nominal intersection point of the two shock waves, allows us to connect the reflection patterns with the six types of shock interference of Edney, which include type I–VI shock interferences depending on how an upstream oblique shock intersects a bow shock (types I and II are regular and Mach reflections of two shocks from the opposite sides; type III and type IV have two triple points or two Mach reflection configuration; type V and type VI are irregular and regular reflections of two shocks from the same side). We are thus able to identify all possible shock reflection types and find their transition conditions. Pre-shock reflection may yield IV, V and VI (of Edney's six types) shock interferences and post-shock reflection may yield I, II and III shock interferences. Pre- and post-shock reflections possibly occur at two different parts of the SOSW, and the complete reflection configuration may have one or both of them. Both transition condition study and numerical simulation are used to show how pre-shock reflection and post-shock reflection exist alone or coexist, leading to various types of combined pre-shock and post-shock reflections.

A Reconfigurable SRAM CRP PUF with High Reliability and Randomness

This paper presents a novel reconfigurable SRAM CRP PUF that can achieve high reliability and randomness. In conventional reconfigurable SRAM CRP PUFs, imprecise timing control can produce a biased response output, which is typically attributed to mismatches in the connection of input control signals to the two inverter arrays in the layout floorplan. We propose a timing control scheme along with the addition of an adjunct NMOS transistor to address this issue. This eliminates the connection mismatches for the challenge and word-line inputs to the two inverter arrays. Furthermore, we employ symmetric layout techniques to achieve the randomness of response output. The symmetric arrangement of the two inverter arrays maximizes the inherent random output characteristics derived from process variation. The pre-charge input signal is symmetrically connected to each array to prevent delay mismatches. A 16 × 9-bit reconfigurable PUF array is fabricated by using a 180 nm CMOS process, with a PUF cell area of 1.2 × 104 F2/bit. The experimental results demonstrate an inter Hamming distance of 0.4949 across 40 chips and an intra Hamming distance of 0.0167 for a single chip in 5000 trials. The measured worst bit error rate (BER) is 4.86% at the nominal point (1.8 V, 25 °C). The proposed prototype exhibits good reliability and randomness, as well as a small silicon area when compared to the conventional SRAM CRP PUFs.

Performance Comparison Between Centralized and Hierarchical Predictive Functional Control for Adaptive Cruise Control Application

This paper presents a performance comparison between two different control structures of Predictive Functional Control (PFC), namely centralized and hierarchical architectures for an Adaptive Cruise Control (ACC) system. Centralized PFC utilizes a linearized model of the vehicle longitudinal dynamics to compute the control law, while hierarchical PFC uses a simple kinematic model with inverse vehicle longitudinal dynamics. Based on the simulation results, both control structures produced a satisfactory performance. However, in the presence of disturbances such as road slopes and wind gusts, the centralized PFC becomes more sensitive and conservative than the hierarchical PFC. The main reason is that the linearization model used in centralized PFC is only effective around the selected nominal operating points. Since the decision-making process depends on the internal model performance, centralized PFC cannot compensate for this effect. Besides, it also takes a longer computation time than hierarchical PFC since more mathematical operations must be solved than the kinematic model, especially when physical and operational constraints are considered. The standard performance parameters such as Root Mean Squared Error (RMSE), settling time, and rise time are also used for the analysis. These findings can become a solid justification for using the hierarchical PFC structure in designing an ACC system for future work.

Super-twisting sliding mode finite time control of power-line inspection robot with external disturbances and input delays

An adaptive super-twisting sliding mode control (AST-SMC) is proposed for the power-line inspection (PLI) robot system with two degrees of freedom and single control input underactuated with multiple balances. Firstly, the nonlinear dynamic equation of PLI robot is established, and the model is linearized at the nominal equilibrium point. Secondly, a special transformation is introduced to transform the original input delay system into a delay-free model, and an equilibrium manifold linearization (EML) model is established by using scheduling variables to expand the operating range of the controlled system, as a result of which the disturbance observer control (DOC) is designed to estimate the external disturbance. Thirdly, in order to achieve fast convergence and continuous control, the super-twisting sliding mode control(ST-SMC) method is proposed to decrease chattering in the control law. Finally, it can be verified by Lyapunov stability theory that the system reaches the sliding mode surface in finite time and the trajectory tracking error converges to zero in finite time. The simulation results verify that the combination of DOC and AST-SMC has a optimal disturbance approximation and control convergence ability, clarifying the effectiveness and robustness of the proposed control scheme.

Health economic analysis of inpatient prostate cancer treatment in Austrian hospitals

Abstract Background Prostate cancer (PrC) is the fourth most prevalent type of cancer worldwide. Its high incidence and 5-year survival rates contributing to high inpatient care costs make it an important public health issue. In Austria, surgery has been the most common inpatient procedure for PrC, despite clinical recommendations not clearly indicating its benefits over alternatives. No health economic comparison of these procedures has considered the period after treatment yet. We bridge this gap by analysing the health economic impact of treatment pathways. Methods We use a large administrative dataset of all inpatient PrC patients in Austria who received either only surgery or only radiation therapy from 2005-2014 (n = 34,286). To assess the health economic impact, we used diagnosis-related-group (DRG) points and length of stay (LOS). Monthly DRG points and LOS for each patient ±12-months around the index procedure were analysed using the difference in difference (DID) method. We controlled for age, and physical comorbidity burden using Charlson Comorbidity Index (CCI) scores. Results Looking at unadjusted averages, patients in the surgery group were significantly younger and had a lower CCI compared to the radiation group. Consequently, the surgery group had lower nominal average DRG points and LOS. However, when controlling for age and CCI, we found that radiation treatment was less resource intensive. A DID estimation found a shorter average LOS and lower DRG points for the radiation group compared to surgery for the 12 months post index. Conclusions We found significant additional costs and LOS times for surgical pathways following risk adjustment in Austria. This implies a potential excess burden of ∼4,400 hospitalisation days and ∼4 million DRG points (€4.8m) a year for the healthcare system during the observed period. Considering international evidence on higher patient burden in surgical pathways, these findings may call for clinical reconsiderations of PrC care. Key messages • Patient characteristics of different inpatient treatment pathways for PrC in Austria were very heterogenous. • Health economic outcomes in the post treatment period for PrC inpatient treatment were significantly better for radiation treatment compared to surgery.

Robust optimization and uncertainty quantification of a micro axial compressor for unmanned aerial vehicles

Axial compressors are susceptible to uncertainties during their manufacturing and operation, resulting in reduced efficiency and performance dispersion. However, uncertainty quantification and robust design of compressors remains challenging due to the complexity of structure and internal flow. In this study, an automated framework for uncertainty quantification and robustness optimization of micro axial compressors is proposed. Ten geometrical uncertainties are propagated for the nominal design point and two off-design points, i.e., near stall and choke conditions, respectively. The main objective of this paper is to optimize the aerodynamic robustness performance at these operating points. The sparse grid-based probabilistic collocation method is used to propagate these uncertainties, and a multi-objective genetic algorithm is employed to perform robust optimization based on a novel constructed surrogate model.The results show that the optimal configuration achieves an improvement in aerodynamic robustness and mean performance across the entire characteristic map, with greater improvement at the design working point than at the off-design points. At the design working point, the mean isentropic efficiency and pressure ratio of the optimal configuration increase by 0.6% and 0.5%, respectively, while the standard deviation of isentropic efficiency, pressure ratio, and mass flow rate decreases by 32.4%, 41.2%, and 25.1%, respectively. This optimization framework proves to be both feasible and efficient and can be applied to aerodynamic robust optimization of turbomachinery. In the future, we will apply this framework to different aspects of the gas turbine life cycle to model and analyze uncertainties of larger orders of magnitude.

Wind power interval and point prediction model using neural network based multi-objective optimization

Wind power point and interval prediction plays an important role in dispatching. However, for obtaining both point estimations and prediction intervals (PIs), the existing models like constructing the probability density function are too complicated. This paper proposes a novel multi-objective upper and lower bound and point estimation (MOULPE) model. It constructs a neural network (NN) with double outputs to directly estimate the prediction intervals (PIs) and the median of PIs is calculated as point estimation. Considering wide decision-making space, the problem formulation of MOULPE is defined as three objectives which covers both evaluation indices of PIs and point prediction. Furthermore, based on elite opposition-based learning (EOBL), this paper improves non-dominated fast sort genetic algorithm-III (INSGA-III) to search the optimal front. Two criteria called prediction interval nominal confidence (PINC) and point prediction nominal error (PPNE) are adopted to pick out the best solution. According to the general requirements in literature, four examples of real wind power data are conducted. Compared with some state-of-the-art methods, the coverage probability of PIs constructed by the proposed model not only reaches the preset PINC, but the average width is also the lowest. Similarly, the point estimation error of the proposed method is less than PPNE.

ANALIZA NUMERICĂ A UNEI NOI CONFIGURAŢII DE TURBINE EOLIENE CU AX VERTICAL

Governmental incentives, technological progress, and lowering costs have made renewable energy more accessible and more affordable for residential areas. Switching to renewable energy sources not only reduces greenhouse gas emissions but also provides long-term financial gains, energy independence, and a cleaner environment for communities. In this study, a numerical analysis of a vertical-axis wind turbine layout that is easily adaptable to populated areas was conducted. Among the results are the variation of the torque coefficient during the course of a complete 360-degree rotation and the vorticity magnitude evolution at the nominal point. In order to validate the numerical results, a test campaign will be conducted inside the wind tunnel as part of further study. This campaign will be carried out using an experimental small-scale model.

Conditional Droop Adjustment for Reliability-Oriented Power Sharing in Microgrids

Power electronic systems are facing the challenge to function more safely and reliably. Reliability-oriented power sharing is thereby employed in multi-converter systems to reduce the cost of end-of-life maintenance. One typical approach is to adaptively adjust the droop gains of the converters solely based on the accumulated damage to the power devices. However, this does not always hold throughout the entire loading profile, possibly ending up with a contradiction from higher reliability. Hence, this paper generalizes the reliability-oriented power sharing by necessitating the adjustment of active droop gains considering the nominal power. Two operation regions are formalized by the nominal point, where the adjustment goes into opposite directions. The principle is validated by short-term experiments and long-term simulations estimating the B10 lifetime (10% probability of failure), revealing the improvement of system-level reliability especially under fluctuating loads or operator commands.

Robust Regulation of a Power Flow Controller via Nonlinear Integral Action

This article considers a robust output set-point tracking problem for an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$m$</tex-math> </inline-formula> -terminal power flow controller (PFC) for meshed dc micro-grids. The PFC is a power electronics device used to control the power flow at a node in the meshed grid and may act as a dc circuit breaker. The system is modeled by state-space bilinear dynamics coupled with a polynomial output. In the proposed design, the plant is first extended with an integral action processing the regulation error. The cascaded model composed of the plant and the integrator is then stabilized using a saturated state-feedback law, designed with a forwarding approach. An anti-windup function is added to cope with transient saturations. A tuning method is proposed to set the controller gains along the available degrees of freedom with respect to a cost function. The stability of the closed loop is guaranteed for any compact set of initial conditions and for small parametric variations around the nominal set point. Experiments have been carried out and these properties are successfully assessed on a tenth-scale experimental setup.

Development of a cooling and power generation prototype integrating an axial micro-turbine in an absorption chiller

The integration of an expander in an absorption machine allows it to produce cooling and electricity simultaneously within the same cycle. This technology holds great potential to harness low-temperature heat sources more efficiently than production with separate cycles. However, very few experimental studies on absorption combined cooling and power production cycles can be found in literature. In order to achieve an in-depth understanding of this technology and of the interactions between power and cooling production sides of the circuit, the integration of an expander into a single stage ammonia water absorption chiller was undertaken through the development of an experimental pilot plant. The peculiar characteristics of the expansion device, as well as the use of a newly developed combined desorber avoiding the presence of a rectifier make the prototype built unique. Design and integration of the expander proved to be very challenging, mainly due to the small size of the application and corrosiveness of the ammonia water mixture. Significant electricity generation losses experienced lead to maximum electrical efficiency of 7% and corresponding maximum power production around 33 W at a lower than expected rotational speed of 20′000 rpm.Despite these difficulties, first experimental measurements have been obtained, giving interesting insights on the functioning of the cycle. Indeed, the impracticability of regulating the ratio between cooling and power production was highlighted, due to the characteristics of the impulse turbine. Opening of the turbine line in the nominal point leads to a reduction of the mass flow rate passing through the cooling line of 65% (i.e., split ratio of 0.35) and a cooling power output decrease of around 57% (from 4.9 to 2.1 kW). Additionally, diverting some of the desorbed vapour to the power production line has important effects on the pressure equilibrium and circulating vapour mass flow rate, increasing from 16.1 kg/h in the simple absorption working mode to 31.1 kg/h in the combined mode in the nominal operating point. Feedback from the pilot plant will be very useful for the further development of the technology.

Aerodynamic Optimization and Fuel Burn Evaluation of a Transonic Strut-Braced-Wing Single-Aisle Aircraft

This paper presents an assessment of the potential fuel burn savings offered by the transonic strut-braced-wing configuration within the single-aisle class of aircraft relative to a modern conventional tube-and-wing aircraft through aerodynamic shape optimization based on the Reynolds-averaged Navier–Stokes equations. A representative strut-braced-wing aircraft is first developed through conceptual multidisciplinary design optimization based on the Airbus A320neo, with current technology levels assumed. A concept for the conventional tube-and-wing configuration is also developed to represent the Airbus A320neo as a performance baseline. Single-point aerodynamic shape optimization is then performed on wing–body–tail models of each aircraft to address aerodynamic design challenges and to provide more accurate performance estimates. Results indicate that shock formation can be mitigated from the wing–strut junction of the strut-braced wing at Mach 0.78 and a relatively high design lift coefficient of 0.750, providing an 8.2% reduction in block fuel over a 1000 n mile nominal mission when compared to the conventional tube-and-wing aircraft. Multipoint aerodynamic shape optimization is then performed to build toward a more credible estimate of fuel burn performance, with results showing a reduction in the fuel burn savings to 7.8% at the nominal design point relative to the conventional tube-and-wing aircraft to maintain a 7.6–8.0% improvement over the envelope of operating conditions, which includes design points at even higher Mach numbers and lift coefficients. These results demonstrate the viability of the transonic strut-braced-wing configuration for transport aircraft within the single-aisle class and its potential for reducing commercial fleet fuel burn.

Predictive Modeling of Out-of-Plane Deviation for the Quality Improvement of Additive Manufacturing

Additive manufacturing (AM) is a new technology for fabricating products straight from a 3D digital model, which can lower costs, minimize waste, and increase building speed while maintaining acceptable quality. However, it still suffers from low dimensional accuracy and a lack of geometrical quality standards. Moreover, there is a need for a robust AM configuration to perform in-situ inspections during the fabrication. This work established a 3D printing-scanning setup to collect 3D point cloud data of printed parts and then compare them with nominal 3D point cloud data to quantify the deviation in all X, Y, and Z directions. Specifically, this work aims at predicting the anticipated deviation along the Z direction by applying a deep learning-based prediction model. An experiment with regard to a human “Knee” prototype fabricated by Fused Deposition Modeling (FDM) is conducted to show the effectiveness of the proposed methods.

Station-keeping for Earth–Moon solar-sail resonant libration point orbits

This paper investigates a dynamical reshaping control method for the station-keeping of unstable resonant libration point orbits (LPO) using the solar radiation pressure (SRP) in the solar-sail-augmented Earth–Moon Quasi-Bicircular Problem. The control strategy aims to reshape the geometrical structures defined by the unstable Floquet modes. Furthermore, asymptotic stability can be achieved by incorporating the central Floquet modes into the procedure. The control variables considered are the two attitude angles of the sail with two scenarios: one with constant lightness number and another with non-constant value. The nominal point, defined as a state on the nominal orbit used to measure the deviation of the spacecraft with respect to the nominal orbit, also plays a role in the stability and convergence rate of the control, and independently of this fact, the Jet Transport technique enables the control laws to be developed in a unified way. In addition, the controllers are obtained as Taylor polynomials in terms of the deviation between the state of the spacecraft and the isochronous point. The numerical simulations analyze the stability, dynamical and long-term behaviors, robustness to orbit determination errors and control costs. The results verify the feasibility of considering SRP for long-term maintenance of LPOs in the Earth–Moon system.

Orthogonal Approximation of Invariant Manifolds in the Circular Restricted Three-Body Problem

Methods to parameterize and approximate the hyperbolic invariant manifolds of particular solutions in the circular restricted three-body problem (CR3BP) are presented in this paper. Analytical representations obtained from these manifold approximations are instrumental in the synthesis of optimal trajectories for cislunar transport. A multivariate Chebyshev series is used to approximate the surfaces, thereby serving as tractable parametric representations of the complex properties of motion. It is demonstrated that the continuum of ballistic capture trajectories and their associated sensitivities on the manifold can be realized in functional form using simple algebraic operations. Two applications making use of the Chebyshev manifold approximations as a terminal constraint surface are presented. The first is a low-thrust trajectory optimization problem formulated such that the optimal free final state lying on the manifold is determined as an additional set of design parameters. The second is a guidance law designed to target the manifold in the vicinity of the nominal patch point. Each of these methods takes advantage of the Chebyshev approximations to provide additional flexibility for mission design in multibody dynamic environments. These applications offer tremendous optimism about the utility of function approximation methods in arriving at a formal representation for the invariant manifolds in the three-body problem for efficient generation of optimal trajectories.

GABABR silencing of nerve terminals.

Control of neurotransmission efficacy is central to theories of how the brain computes and stores information. Presynaptic G-protein coupled receptors (GPCRs) are critical in this problem as they locally influence synaptic strength and can operate on a wide range of time scales. Among the mechanisms by which GPCRs impact neurotransmission is by inhibiting voltage-gated calcium (Ca2+) influx in the active zone. Here, using quantitative analysis of both single bouton Ca2+ influx and exocytosis, we uncovered an unexpected non-linear relationship between the magnitude of action potential driven Ca2+ influx and the concentration of external Ca2+ ([Ca2+]e). We find that this unexpected relationship is leveraged by GPCR signaling when operating at the nominal physiological set point for [Ca2+]e, 1.2 mM, to achieve complete silencing of nerve terminals. These data imply that the information throughput in neural circuits can be readily modulated in an all-or-none fashion at the single synapse level when operating at the physiological set point.