Stability Considerations Research Articles

The contribution mechanism of furfuryl alcohol treatment on the dimensional stability of plantation wood

Furfuryl alcohol polymers (PFA) derived from lignocellulosic biomass have been confirmed as an effective modifier to improve dimensional stability of wood. However, the main reason for the dimensional stability related to this method has remained unclear. In this study, principal consideration of dimensional stabilization was analyzed by a mathematics model regarding anti-swelling efficiency (ASE) and cell wall bulking of furfurylated woods with different weight gain precents (WPGs), and ASE’ obtained by method of Ohmae et al. Simultaneously, confocal laser scanning microscopy and nanoindentation technique were applied to explain the dimensional stability mechanism. Results showed that both ASE and cell wall bulking increased with WPG at 0–69%. A nearly linear (R2 = 0.9690) relationship was observed between ASE and cell wall bulking. ASE’ values at different WPGs were approaching zero. The dimensional stability was dominated by cell wall bulking analyzed through both the mathematical model and small ASE’ values at various WPG. In this study, the mechanistic insights into dimensional stabilization of furfurylated wood could provide highly beneficial for controlling the dimensional stability by cell wall bulking.

Topology optimization of trusses incorporating practical local buckling stability considerations

For the practical application of optimized truss structures, the local stability of the bar must be considered to obtain stable and realistic structures. However, in the practical design of structures, the initial crookedness of the bars and residual stresses that remain in the bar after the manufacturing process should be taken into account, which makes the buckling strength highly non-connected and non-convex in terms of the cross-sectional properties. Therefore, most conventional truss optimization formulations include only local buckling constraints based on the Euler buckling criterion, while local buckling constraints based on design specifications are rarely incorporated. To treat these problems, a novel topology optimization model for trusses is proposed, where the critical buckling strength is calculated according to the practical design code GB5007-2017. In addition, a linearized iterative allowable stress method is used to solve the optimization model. Since the allowable stresses are calculated at each iteration based on the critical buckling strength, other types of design codes can also be incorporated into the proposed truss topology optimization model. The proposed computational model shows, through several numerical examples, the remarkable effect of including local buckling stability in the optimal design of trusses, while demonstrating that the optimized topology depends on whether the local buckling constraints are derived from the Euler buckling criterion or from actual structural design codes.

Smart deployment of IoT-TelosB service care StreamRobot using software-defined reliability optimisation design

Intelligent service care robots have increasingly been developed in mission-critical sectors such as healthcare systems, transportation, manufacturing, and environmental applications. The major drawbacks include the open-source Internet of Things (IoT) platform vulnerabilities, node failures, computational latency, and small memory capacity in IoT sensing nodes. This article provides reliable predictive analytics with the optimisation of data transmission characteristics in StreamRobot. Software-defined reliable optimisation design is applied in the system architecture. For the IoT implementation, the edge system model formulation is presented with a focus on edge cluster log-normality distribution, reliability, and equilibrium stability considerations. A real-world scenario for accurate data streams generation from in-built TelosB sensing nodes is converged at a sink-analytic dashboard. Two-phase configurations, namely off-taker and on-demand, link-state protocols are mapped for deterministic data stream offloading. An orphan reconnection trigger mechanism is used for reliable node-to-sink resilient data transmissions. Data collection is achieved, using component-based programming in the experimental testbed. Measurement parameters are derived with TelosB IoT nodes. Reliability validations on remote monitoring and prediction processes are studied considering neural constrained software-defined networking (SDN) intelligence. An OpenFlow-SDN construct is deployed to offload traffic from the edge to the fog layer. At the core, fog detection-to-cloud predictive machine learning (FD-CPML) is used to predict real-time data streams. Prediction accuracy is validated with decision tree, logistic regression, and the proposed FD-CPML. The data streams latency gave 40.00%, 33.33%, and 26.67%, respectively. Similarly, linear predictive scalability behaviour on the network plane gave 30.12%, 33.73%, and 36.15% respectively. The results show satisfactory responses in terms of reliable communication and intelligent monitoring of node failures.

Aerodynamic Design Consideration for Stability of a Lightweight Solar-Powered Aircraft

Aerodynamic design analysis was conducted for the stability of a lightweight solar aircraft weighing 3 kg and a wingspan of 3.2 m. Airfoil analysis was conducted on four selected airfoils. The following factors were considered: good aerodynamic characteristics, low Reynolds number, high lift, low drag, high lift-to-drag ratio, quiet moment coefficient, moderate thickness, and camber curvature. WE-3.55.93 airfoil was selected as best and used to design the wing, and NACA 0008 was used to develop the empennage. The fuselage was designed with two compartments 1.9 m long, and the second compartment is made of aluminium or carbon fibre to reduce weight. The first compartment was 0.95 m long and 0.4 m in diameter. The centre of gravity was determined for the importance of the various aircraft components to ensure aerodynamic stability and balance. The complete assembly was designed using XFLR5 v6 software.

P203 CHALLENGES IN THE MANAGEMENT OF RECTUS MUSCLE HEMATOMA DURING TRIPLE ANTITHROMBOTIC THERAPY IN RECENT ANTERIOR STEMI COMPLICATED BY LEFT ENDOVENTRICULAR THROMBOSIS

Abstract A 69–year–old woman suffering from hypercholesterolemia, GERD, was admitted to our department for anterior ST elevation myocardial infarction and was treated with primary PCI and DES on the mid–distal LAD. Dual antiplatelet therapy (DAPT) with ticagrelor and cardioaspirin was started. The pre–discharge echocardiogram (echo) showed the presence of left ventricular thrombus (LVT) and anticoagulant therapy (enoxaparin and warfarin) was started. On the 9th day the patient complained abdominal pain with onset of chills and hyperthermia and was suspected an uro–septic fever. The day after a mass appeared on the right abdominal wall at the site of the enoxaparin injection and abdominal contrast CT showed a mass of inhomogeneous density, actively supplied by the inferior epigastric artery and its terminal branches, indicative of hematoma of the abdominal rectus muscle. Anticoagulant therapy was suspended. Interventional radiologists in consideration of clinical stability and stable Hb value and the absence of the signs of active arterial bleeding on CT have not indicated an urgent endovascular treatment and DAPT with clopidogrel and cardioaspirin was continued. After V days, echo showed persistent pedunculated and mobile LVT and aspirin was therefore suspended and anticoagulant therapy was reintroduced with fondaparinux 2.5 mg daily. After two days, considering the stability of hematoma dimensions and the Hb values but the persistence of the extremely floating LVT, fondaparinux was increased at dose of 5 mg daily. In the following days, echo showed LVT reworking until its complete disappearance. On the 32th day blood test showed significant reduction in Hb values and a contrast CT showed an increase in size of the hematoma and resumption of micro bleeding. Fondaparinux was stopped and the patient was transferred to the interventional radiology center. Angiography highlights point–like spreads of extravascular contrast from branches of the inferior epigastric artery and branches of the external circumflex iliac artery. Embolization was performed. After a close monitoring of the hemoglobin values and of the echo which showed no LVT and recovery of LV function, in consideration of her thrombotic and hemorragic risks, she was discharged with DAPT with clopidogrel and low dose of aspirin. Abdominal wall hematoma may be a rare complication of subcutaneous enoxaparin therapy especially in STEMI patients undergoing also a DAPT therapy.

Path tracking of autonomous vehicle based on adaptive preview trajectory planning with the consideration of vehicle stability

The path control gives the target path through planning, and uses the tracking strategy to make the vehicle converge to the target path. How to balance the tracking performance and the vehicle stability is a crucial and worthy research for the autonomous vehicle safety. In this paper, a hierarchical path control strategy consists of path planning and tracking with the consideration of vehicle lateral stability is proposed. In the adaptive preview distance block, the preview distance is adaptively regulated according to the vehicle speed, sideslip angle, and the preview trajectory curvature to balance the tracking error and stability. In the path planning block, the three-order polynomial fitting method is adopted to give the desired path according to the preview distance and the relative position relationship between vehicle and road or obstacles. The linear quadratic regulator (LQR) controller is designed to tracking the desired path fully using the previewed curvatures and the vehicle motion error. The hardware in the loop (HIL) simulation and vehicle test results illustrate that the proposed strategy can deal with path tracking, avoidance and lance change scenes in low computation burden, and maintain the stability of vehicle simultaneously.

Current Training and Validation Weaknesses in Classification-Based Radiation Fog Nowcast Using Machine Learning Algorithms

Abstract Large inaccuracies still exist in accurately predicting fog formation, dissipation, and duration. To improve these deficiencies, machine learning (ML) algorithms are increasingly used in nowcasting in addition to numerical fog forecasts because of their computational speed and their ability to learn the nonlinear interactions between the variables. Although a powerful tool, ML models require precise training and thoroughly evaluation to prevent misinterpretation of the scores. In addition, a fog dataset’s temporal order and the autocorrelation of the variables must be considered. Therefore, classification-based ML related pitfalls in fog forecasting will be demonstrated in this study by using an XGBoost fog forecasting model. By also using two baseline models that simulate guessing and persistence behavior, we have established two independent evaluation thresholds allowing for a more assessable grading of the ML model’s performance. It will be shown that, despite high validation scores, the model could still fail in operational application. If persistence behavior is simulated, commonly used scores are insufficient to measure the performance. That will be demonstrated through a separate analysis of fog formation and dissipation, because these are crucial for a good fog forecast. We also show that commonly used blockwise and leave-many-out cross-validation methods might inflate the validation scores and are therefore less suitable than a temporally ordered expanding window split. The presented approach provides an evaluation score that closely mimics not only the performance on the training and test dataset but also the operational model’s fog forecasting abilities. Significance Statement This study points out current pitfalls in the training and evaluation of pointwise radiation fog forecasting with machine learning algorithms. The objective of this study is to raise awareness of 1) consideration of the time stability of variables (autocorrelation) during training and evaluation, 2) the necessity of evaluating the performance of a fog forecasting model in direct comparison with an independent performance threshold (baseline model) that evaluates whether the fog forecasting model is better than guessing, and 3) the fact that prediction of fog formation and dissipation must be evaluated separately because a model that misses all of these transitions can still achieve high performance in the commonly used overall evaluation.

In-situ STEM study on thermally induced phase transformation of magnetic (Nd0.75Ce0.25)2Fe14B ribbons

Studying the phase transformation and microstructure evolution of magnetic Nd-Ce-Fe-B nanocrystalline melt-spun ribbon is of paramount significance in developing this important class of magnetic materials. In this work, the thermal-induced phase transformation of (Nd0.75Ce0.25)2Fe14B nanocrystalline sample was revealed via in-situ heating scanning transmission electron microscopy (STEM) experiment (RT-750 ℃). Starting from a single-phase (Nd0.75Ce0.25)2Fe14B nanocrystalline matrix at room temperature (RT), grain boundary (GB) diffusion behavior was investigated at an atomic scale. Our result shows that the rare earth elements accumulate at GB area from 200 °C and form a uniform thin amorphous layer between grains. The decomposition of the primary phase was observed at about 350 ℃ and crystalized as BCC-Fe, Fe2B, and (Nd0.75Ce0.25)2O3 phases driven by thermal activation at a higher temperature. This work provides the essential information of phase transformation and microstructure evolution of NdCeFeB-based magnets at high temperatures and new insights into thermal treatment designing and thermal stability considerations.

Path tracking of autonomous vehicle with consideration of vehicle stability in sideslip angle phase plane

In current research of autonomous vehicle path tracking, most contributions focus on tracking accuracy during complex driving condition. However, the vehicle might fall into unstable dangerous condition when the road curvature is big or with high speed. A path tracking control framework is proposed in this paper, which considers path tracking accuracy and vehicle stability. In general, the control framework consists of three main components: vehicle stability judging controller, path tracking controller, and torque distributor. Firstly, the stability of the current vehicle can be evaluated by the stability judgment controller according to the phase plane of the sideslip angle. Then, the proportion of vehicle stability in the control objective is adjusted according to the current vehicle stability. To improve the path tracking accuracy, the path tracking is composed of a combined controller using MPC algorithm, which controls the front wheel angle and direct yaw moment at the same time. After that, the torque distributor is developed to distribute the desired yaw moment into four executive wheels, which synthesizes the results of power performance distribution and stability distribution. Finally, the effectiveness of the proposed control framework is verified by the Matlab-CarSim co-simulation experiment and the hardware-in-the-loop experiment based on LabVIEW-RT. The results show that the proposed controller has better tracking accuracy and stability than the general MPC controller.

Cant angle morphing winglets investigation for the enhancement of the aerodynamic, stability and performance characteristics of a tactical Blended-Wing-Body UAV

The current study presents the investigation of the cant angle morphing winglet concept on a tactical, fixed-wing, Blended-Wing-Body (BWB) Unmanned Aerial Vehicle (UAV). The potential of the cant angle morphing winglet concept is assessed at various operating conditions, also including critical stability and trimming considerations. The objectives of this work are 1) to show the importance of including all key metrics (aerodynamics, performance, stability) into the evaluation process and 2) to propose an efficient methodology that allows this evaluation to be conducted. The cant angle is defined as the primary morphing winglet parameter and a total of 7 alternative configurations are generated. These configurations are investigated using high-fidelity, computational modeling (Computational Fluid Dynamics – CFD). The CFD results are in turn used to develop a surrogate model, so that the evaluation of the cant angle morphing winglet can be conducted throughout the entire cant angle range. The evaluation is conducted in three main steps, the first of which is a calculation of the changes in aerodynamic efficiency and corresponding net performance results. In the second step, some key stability-related constraints are also introduced and, at the third step, the effect of trimming is applied. The results for each of the three steps are presented in detail and are accompanied by a dedicated comparison section. An important conclusion of this work is that the stability aspects can by no means be ignored, since they drastically affect the cant angle morphing aerodynamic efficiency and performance enhancement potential.

Stability bounds on superluminal propagation in active structures

Active materials have been explored in recent years to demonstrate superluminal group velocities over relatively broad bandwidths, implying a potential path towards bold claims such as information transport beyond the speed of light, as well as antennas and metamaterial cloaks operating over very broad bandwidths. However, causality requires that no portion of an impinging pulse can pass its precursor, implying a fundamental trade-off between bandwidth, velocity and propagation distance. Here, we clarify the general nature of superluminal propagation in active structures and derive a bound on these quantities fundamentally rooted into stability considerations. By applying filter theory, we show that this bound is generally applicable to causal structures of arbitrary complexity, as it applies to each zero-pole pair describing their response. As the system complexity grows, we find that only minor improvements in superluminal bandwidth can be practically achieved. Our results provide physical insights into the limitations of superluminal structures based on active media, implying severe constraints in several recently proposed applications.

Analytical Methods of Voltage Stability in Renewable Dominated Power Systems: A Review

The ongoing development of renewable energy and microgrid technologies has gradually transformed the conventional energy infrastructure and upgraded it into a modernized system with more distributed generation and localized energy storage options. Compared with power grids utilizing synchronous generation, inverter-based networks cannot physically provide large amounts of inertia, which means that more advanced and extensive studies regarding stability considerations are required for such systems. Therefore, appropriate analytical methods are needed for the voltage stability analysis of renewable-dominated power systems, which incorporate a large number of inverters and distributed energy sources. This paper provides a comprehensive literature review of voltage stability analyses of power systems with high levels of renewable energy penetration. A series of generalized evaluation schemes and improvement methods relating to the voltage stability of power systems integrated with various distributed energy resources are discussed. The existing voltage stability analysis methods and corresponding simulation verification models for microgrids are also reviewed in a systematic manner. The traditional and improved voltage stability analysis methods are reviewed according to the microgrid operation mode, the types of distributed generators, and the microgrid configurations. Moreover, the voltage stability indices, which play a crucial role in voltage stability assessments, are critically evaluated in terms of the applicable conditions. The associated modeling and simulation techniques are also presented and discussed. This contribution presents guidelines for voltage stability analysis and instability mitigation methods for modern renewable-rich power systems.

Does monetary policy affect bank lending to households and firms differently?

Are the bank lending channel effects of monetary policy different on bank loans to households and firms? This question has an implication for the financial stability consideration of monetary policy but is not answered in previous literature. We examine Korean banks’ monthly financial statements from 2010 to 2019 based on the identification strategy that compares banks with different balance sheet liquidities. We find that the bank lending channel is significant in business loans but not in household loans. The difference in policy effects is related to the different maturity structures. Monetary policy changes take effect in bank loans primarily through new/refinanced loans. The share of these new loans is larger in business loans than in household loans because loan maturities are shorter for firms. We provide supporting evidence by examining the data on loan maturity and new mortgage loans.

Developing large-scale molecular stability engines for clinical variant interpretation

Computational models that aim to predict the impact of an amino acid substitution on the structure and function of human proteins using molecular stability considerations are widely available (for example, SIFT and Polyphen2). In clinical missense variant interpretation however, these models are typically considered to have too weak a predictive value to be of high utility. However, when there is sufficient protein structure data and feature support for a given transcript, a model using a molecular stability engine (MSE) can reach a predictive value high enough to be used in clinical variant interpretation.

Financial Stability Considerations for Monetary Policy: Empirical Evidence and Challenges

<ns3:p>This paper reviews literature on the empirical relationship between vulnerabilities in the financial system and the macroeconomy, and how monetary policy affects that connection. Financial vulnerabilities build up over time, with both risk appetite and risk taking rising during economic expansions. To some extent, financial crises are predictable and have severe real economic consequences when they occur. Empirically it is difficult to link monetary policy to financial vulnerabilities, in part because financial cycles have long durations, making it difficult to separate effects of changes in monetary policy from other business cycle effects.</ns3:p>

Financial Stability Considerations for Monetary Policy: Theoretical Mechanisms

<ns3:p>This paper reviews the theoretical literature at the intersection of macroeconomics and finance to draw lessons on the connection between vulnerabilities in the financial system and the macroeconomy, and on how monetary policy affects that connection. This literature finds that financial vulnerabilities are inherent to financial systems and tend to be procyclical. Moreover, financial vulnerabilities amplify the effects of adverse shocks to the economy, so that even a small shock to fundamentals or a small revision of beliefs can create a self-reinforcing feedback loop that impairs credit provision, lowers asset prices, and depresses economic activity and inflation. Finally, monetary policy may affect the buildup of vulnerabilities, but the sign of the impact along some of its transmission channels is theoretically ambiguous and may vary with the state of the economy.</ns3:p>

Forced Solid-State Oxidation Studies of Nifedipine-PVP Amorphous Solid Dispersion.

In the present study, the oxidative degradation behavior of nifedipine (NIF) in amorphous solid dispersions (ASDs) prepared with poly(vinyl pyrrolidone) (PVP) with a short (K30) and a long (K90) chain length was investigated. The ASDs were prepared via dry ball-milling and analyzed using Fourier transform infrared (IR) spectroscopy, X-ray scattering, and differential scanning calorimetry. The ASDs were exposed to accelerated thermal-oxidative conditions using a pressurized oxygen headspace (120 °C for 1 day) and high temperatures at atmospheric pressure (60-120 °C for a period of 42 days). Additionally, solution-state oxidative degradation studies showed that pure NIF degrades to a greater extent than in the presence of PVP. Electronic structure calculations were performed to understand the impact of drug-polymer intermolecular interactions on the autoxidation of drugs. While no drug degradation was observed in freshly prepared ASD samples, alkyl free radicals were detected via electron paramagnetic resonance (EPR) spectroscopy. The free radicals were found to be consumed to a greater extent by PVP K30- than PVP K90-based ASDs upon exposure to high oxygen pressures. This was consistent with the greater solid-state oxidative degradation of NIF observed in ASDs with PVP K30 than with PVP K90. As no drug recrystallization occurred during this study period, the lower glass-transition temperature and presumed greater molecular mobility of PVP K30 and its ASD as compared to the PVP K90 system appear to contribute to the greater drug degradation in PVP-K30-based ASDs. The extent and the rate of oxidative degradation were higher in the case of PVP-K30-based ASD as compared to that in PVP-K90-based ASD, and the overall degradation increased with an increase in temperature. IR spectral analysis of drug-polymer interactions supports the electronic calculations of the oxidation process. We infer that, apart from the initial free radical content, the difference in the extent of drug-polymer intermolecular interactions in ASDs and amorphous stabilization during the forced oxidation experiments contribute to the observed differences in the autoxidative reactivity of the drug in ASDs with different PVP chain lengths. Overall, the chemical degradation of NIF in ASDs with two PVP chain lengths obtained from accelerated solid-state oxidation studies was in qualitative agreement with that obtained from long-term (3 years) storage under ambient conditions. The study highlights the ability of accelerated processes to determine the oxidative degradation behavior of polymeric ASDs and suggests that the polymer chain length could factor into chemical as well as physical stability considerations.

A Noniterative Problem-Dependent Formula for Stiff Dynamic Problems

Abstract A novel one-step formula is proposed for solving initial value problems based on a concept of eigenmode. It is characterized by problem dependency since it has problem-dependent coefficients, which are functions of the product of the step size and the initial physical properties to define the problem under analysis. It can simultaneously combine A-stability, explicit formulation, and second-order accuracy. A-stability implies no limitation on step size based on stability consideration. An explicit formulation implies no nonlinear iterations for each step. The second-order accuracy with an appropriate step size can have good accuracy in numerical solutions. Thus, it seems promising for solving stiff dynamic problems. Numerical tests affirm that it can have the same performance as that of the trapezoidal rule for solving linear and nonlinear dynamic problems. It is evident that the most important advantage is of high computational efficiency in contrast to the trapezoidal rule due to no nonlinear iterations of each step.

Stable electromagnetic interactions with effective media of active multilayers

Gain is a blessing and a curse for photonic designs; indeed, gain-based devices may become unprecedentedly efficient but, on the other hand, the local electromagnetic fields can increase exponentially with time and lead the systems to instability. Such stability considerations are presented for a homogenized configuration incorporating tilted active multilayers by determining the poles of its transfer functions across the complex frequency plane and analytically deriving the respective constraints. The reported stable regimes will be crucial in tuning the examined module when incorporated in photonic setups for serving multiple purposes from filtering and imaging to cloaking and lasing.

Competition between Entrainment Phenomenon and Chaos in a Quantum-Cascade Laser under Strong Optical Reinjection

The topic of external optical feedback in quantum-cascade lasers is relevant for stability and beam-properties considerations. Albeit less sensitive to external optical feedback than other lasers, quantum-cascade lasers can exhibit several behaviors under such feedback, and those are relevant for a large panel of applications, from communication to ranging and sensing. This work focused on a packaged Fabry–Perot quantum-cascade laser under strong external optical feedback and shows the influence of the beam-splitter characteristics on the optical power properties of this commercially available laser. The packaged quantum-cascade laser showed extended conditions of operation when subject to strong optical feedback, and the maximum power that can be extracted from the external cavity was also increased. When adding a periodic electrical perturbation, various non-linear dynamics were observed, and this complements previous efforts about the entrainment phenomenon in monomode quantum-cascade lasers, with the view of optimizing private communication based on mid-infrared quantum-cascade lasers. Overall, this work is a step forward in understanding the behavior of the complex quantum-cascade-laser structure when it is subjected to external optical feedback.