Time Delay Research Articles

Optimally tuned cascaded FOPI-FOPIDN with improved PSO for load frequency control in interconnected power systems with RES

In the operation and control of power systems, load frequency control (LFC) plays a critical role in ensuring the stability and reliability of interconnected power systems. Modern power systems with significant penetration of highly variable and intermittent renewable sources present new challenges that make traditional control strategies ineffective. To address these new challenges, this paper proposes a novel LFC strategy that employs a cascaded fractional-order proportional integral-fractional-order proportional integral derivative with a derivative filter (FOPI-FOPIDN) as a controller. The parameters of the FOPI-FOPIDN are optimised using a variant of the particle swarm optimization (PSO) in the literature called ADIWACO. The effectiveness and scalability of the proposed strategy are validated by extensive simulations conducted on two- and three-area test systems and performance comparisons with recent LFC control strategies in the literature. The performance metrics used for the evaluation are ITAE values, deviations in the power flows in the tie-lines, and deviations in the frequencies of the control areas with the power systems subjected to diverse load and RES generation disturbances in several experimental scenarios. Governor dead band, communication time delay, and generation rate constraints are considered in one of the scenarios for more realistic evaluation. Again, the controller’s robustness to uncertain model parameters is validated by varying the parameters of the three-area test system by ± 50%. The simulation results obtained confirm the controller’s robustness and its superiority over the comparison LFC strategies in terms of the above performance metrics.

Uncertainty quantification and data consistency analysis for the development of hydrogen and syngas oxidation model

The exponential growth of contemporary chemical kinetics data coupled with the potential inherent high uncertainty poses significant challenges for developing chemical kinetic models. To obtain a high-quality dataset for the optimization of H2 and syngas oxidation model, this study developed a framework for data consistency analysis and uncertainty analysis of chemical kinetic data. The framework combines simulations based on solving conservation equations, data-driven metaheuristic algorithms, and statistical analysis. Over 2000 experimental data points, including ignition delay times measured in shock tubes, laminar flame speeds, and concentration profiles measured in perfectly stirred reactors and plug flow reactors, were collected and used to construct the experimental dataset. Seventeen parameters of a detailed H2 and syngas oxidation model were selected to build the reaction rate constant (RRC) dataset. The initially estimated experimental uncertainties and RRC uncertainty factors were updated by slack variables in the iterative algorithm. Some high-uncertainty data were identified and excluded from the optimization dataset. The final experimental dataset achieves data consistency, and the feasible parameter set of RRC shows good prediction capability. The experimental data with high uncertainties were highlighted, and the uncertainty sources were analyzed.

Crystallization and microwave dielectric properties of CaO-B2O3-SiO2 glass-ceramic/Al2O3 for LTCC applications

High-frequency electronic devices with low dielectric loss and electronic components with high integration densities require high-performance electronic packaging materials. In this study, materials primarily composed of CaO-B2O3-SiO2 (CBS) with an elevated boron content were fabricated through solid-phase sintering using Al2O3 as the ceramic phase. The phase compositions, densification process, microstructures, thermal conductivity, thermal expansion, and dielectric properties of the LTCC were investigated. Remarkably, the CBS-1 LTCC composite sintered at 850 °C for 4 h, exhibited a dense and nonporous microstructure. It demonstrated exceptional thermoelectric properties, including a thermal shrinkage of 5.61 %, coefficients of thermal expansion of 4.86 ppm/°C, thermal conductivity of 2.36 W/m·K, dielectric constant (εr) of 4.88, and tan δ of 1.05× 10−3 at 15 GHz. These characteristics are conducive to minimizing the signal propagation time delay and filtering noisy signals. Consequently, the CBS-1 LTCC composite emerged as a promising substrate for LTCC applications.

Process simulation of laser shock-based disassembly of adhesively bonded composite/metallic structural parts: a numerical upscaling

ABSTRACT In previous works, both experimental and numerical investigations have shown the potential of the laser shock technique for disassembling adhesively bonded composite/metal coupons. This study extends this concept to upscale the method, focusing on the full disassembly of a foreign object damage (FOD) panel designed to replicate an aircraft engine fan blade. Utilizing LS-Dyna explicit FE software, the numerical simulation incorporates various material models: a progressive damage model for the 3D CFRP substrate, Johnson–Cook plasticity model combined with Grüneisen equation of state for the titanium layer, and a cohesive zone model with a bilinear traction separation law for the adhesive layer. Investigating the FOD panel’s inclined geometry, a preliminary analysis examines the impact of inclination angles on shock wave propagation and back face velocity, revealing minimal alterations. Initial simulations are conducted to determine double pulse delay times and evaluate spot location effects. Automation of the multi-step process simulation is achieved through a Python script. After approximately 30 shots, complete disassembly of the FOD strip is achieved, with observed damage primarily limited to matrix cracking in the composite substrate. Numerical findings support the efficacy of the double-shot laser shock method for disassembling adhesively bonded metallic/CFRP components, contingent upon appropriate experimental arrangements.

Factors of cancer diagnosed family and medical system for delay in diagnosis and treatment of esophageal cancer

Introduction. The esophagus cancer patients needs early diagnosis to achieve better prognosis. The delay barriers increase progression of diseases to higher stages. The aim of work was to identify and explore the barriers in diagnosis of esophagus cancer and chart the time duration in this process. Material and Methods. The study was conducted in Jinnah Hospital Lahore (JHL), a teaching care hospital of Allama Iqbal Medical College, during a period of one year from July 2019 to July 2020. There were 49.42 % female and 50.57 % male patients. Results. Mean age found to be 56 years. Mean Total delay (TD ) time was 206 days and median Total delay (TD ) time in days were 197 days with 25th and 75th (157, 246) percentiles respectively. Longest delays were found in 51–60 age group and age related (r=0.94) significantly to delays (p=0.0004). Initial symptom of weight loss shows maximum delay and symptoms are highly correlated (r=0.94) with delay (p=0.004). The low income group presents maximum delay. Mean patient delay (PD ) time in days were 142 days with 135 Median and (88, 195) 25th and 75th percentile respectively. Mean, Median, 25th and 75th percentiles for Physician delays (PhyD) times were (20, 18, 16, 23) respectively. Treatment delay (TD ) time (Mean, Median) in days were (18, 18.52) with 25th and 75th (14, 22) percentiles. The education significantly reduces the delays with correlation (r=0.91) and significance (p=0.02). Mean system delay (SD ) time were 25 days and median were 24 days with 25th and 75th (20, 31) percentiles. Conclusion. Illiteracy, financial problems, and unavailability of information related to the cancer and health care system, very limited number of health facilities remains the main causes of these delays.

Lyapunov functionals for a virus dynamic model with general monotonic incidence, two time delays, CTL and antibody immune responses

In this paper, we study global asymptotic stability of all equilibria of a virus dynamic model with general monotonic incidence, two time delays, CTL and antibody immune responses by constructing Lyapunov functionals and applying LaSalle’s invariance principle.

The dynamic analysis of the rumor spreading and behavior diffusion model with higher-order interactions

Rumor spreading occurs not only between two individuals but also among multiple individuals or influenced by groups. However, pairwise interactions in complex networks are insufficient to describe this process. In this study, we propose a rumor spreading model with higher-order interactions, in which the rumor propagation process is represented by simplicial complexes. By selecting the propagation coefficient and time delay as the threshold, the model shows richer dynamic behaviors, such as the bi-stability, discontinuous transition, forward bifurcation, backward bifurcation, Hopf bifurcation, and periodic oscillation. Besides, for exploring the collective behavior induced by rumors, the rumor synchronization model is first established by applying the adaptive feedback mechanism, which erects a theoretical bridge between rumor spreading and behavior diffusion. Moreover, an improved optimal control strategy considering system gains is performed to curb rumor diffusion. Numerical simulations suggest that rumor spreading models with higher-order interactions are more consistent with actual data than network-based ones. Our results may shed some light on comprehending higher-order interactions in rumor spreading and the coupling between rumor and behavior, and provide a promising approach to control rumors and irrational behaviors.

Stability and stabilization for the hydraulic automatic gauge control system of cold rolling mill with time delay and saturation

This paper studies the stability and stabilization of hydraulic automatic gauge control (HAGC) systems with time-varying delay and actuator saturation. First, a mathematical model of HAGC systems is established considering the measurement delay and saturation factors. With the help of state transformation, the measurement delay is transformed into input delay and the generalized sector condition is adopted to deal with the saturation problem in HAGC systems. Then, a new augmented L–K functional is constructed to contain more delay information to reduce the conservativeness of the stability criteria. Furthermore, by combining the proposed L–K functional with some advanced inequalities, the stability conditions and controller are derived with the aid of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed control algorithm is verified by simulation results.

NOx concentration prediction based on multi-channel fused spectral temporal graph neural network in coal-fired power plants

Establishing an accurate and stable NOx concentration prediction model is the foundation for achieving environmental protection in coal-fired power plant denitrification. In this research, a data-driven hybrid prediction model (BMFE-MFST-GNN) is proposed to improve the prediction accuracy of inlet NOx concentrations. First, we develop the adaptive variational modal decomposition method (FEVMD) to decompose historical NOx concentration data into simple and smooth subsequences and extract time-frequency features. Second, we propose the boosting mutual information feature selection algorithm (BMIFS) to determine the best set of auxiliary variables. The delay time is calculated based on the maximal information coefficient (MIC) to reconstruct the datasets. Then, the multi-channel fused spectral temporal graph neural network (MFST-GNN) is created to build the graph feature information of decomposed subsequences and reconstructed auxiliary variables to predict the concentration subsequences. Finally, we integrate the subsequence prediction results to obtain the future NOx concentrations. The experimental results demonstrate that the proposed method outperforms several comparative models in predicting NOx concentrations.

Enhancement noise margin and delay time performance of novel punch-through nMOS for single-carrier CMOS

In this paper, we propose the use of punch-through nMOS (PTnMOS) as an alternative to pMOS in complementary metal oxide semiconductor (CMOS) circuits. According to the TCAD simulation results, PTnMOS exhibit sub-threshold characteristics similar to those of pMOS and can be formed by simply changing the doping concentration of the source and drain. Without the need for sizing, which solves the area occupation problem caused by the need to increase the width of pMOS due to insufficient hole mobility. In addition, we compose a PTnMOS and nMOS without sizing to form a single-carrier CMOS in which only electrons are transmitted, and We extract its performance for comparison with conventional CMOS (Wp/Wn = 1). The results indicate that single-carrier CMOS has symmetric noise margin and 29% faster delay time compared to conventional CMOS (Wp/Wn = 1). If III–V or II–VI group materials could be applied to single-carrier CMOS, not only could costs be reduced and wafer area occupancy minimized, but also significant improvements in the performance and bandwidth application of microwave circuits could be achieved.

Distributed delayed impulsive control for [formula omitted]-synchronization of multi-link structure networks with bounded uncertainties and time-varying delays of unmeasured bounds: A novel Halanay impulsive inequality approach

This study discusses the μ−synchronization of multi-link structure networks with parameter uncertainties and nonlinear couplings. Three types of variable delays, including internal, coupling, and distributed delays at sampling moments are deliberated in the synchronization control process. Different from existing multi-link models, the bulk of delays can be non-differentiable and unmeasured, which also brings new challenges to our research. To conquer the difficulties caused by such multiple generalized time delays, a novel Halanay-like impulsive inequality is established by utilizing the properties of μ−function and mathematical induction recipes. For letting the multi-link networks achieve μ−synchronization, a distributed-delay impulsive controller is designed, and multiple coupling matrices are decomposed into diagonal matrices and residual matrices. Based on the stability function method, the derived impulsive inequality, and matrix decomposition techniques, important synchronization conditions for the concerning multi-link networks are obtained, which releases the traditional constraints that delays should be smaller than impulsive intervals, and popularizes the existing synchronization results respecting multi-link systems with unbounded delays.

Ultimate boundedness and stability of highly nonlinear neutral stochastic delay differential equations with semi-Markovian switching signals

The ultimate boundedness and stability of highly nonlinear neutral stochastic delay differential equations (NSDDEs) are investigated in this paper. Different from many previous works, the highly nonlinear NSDDEs with semi-Markov switching signals are considered for the first time in this paper. Meanwhile, the time delay function in this paper is only required to meet much more relaxed restrictions, which can invalidate plentiful methods with requirements on its derivatives for the stability of NSDDEs. To overcome this difficulty, several novel techniques to tackle NSDDEs with such a delay are developed. Furthermore, a crucial property on the ergodic semi-Markov process is established, which plays a key role in the proof on the existence and boundedness of global solution. The generalized Khasminskii-type theorems are established for the existence and uniqueness of global solution by applying new methods and this property, and the criteria for boundedness and stability are also provided. In particular, feasible measures are provided to deal with the neutral term in our stability criteria. Finally, the effectiveness is verified by a numerical example.

Distributed State Observer for Systems with Multiple Sensors under Time-Delay Information Exchange.

The issues of state estimations based on distributed observers for linear time-invariant (LTI) systems with multiple sensors are discussed in this paper. We deal with the scenario when the information exchange has known time delays, and aim at designing a distributed observer for each subsystem such that each distributed observer can estimate the system state asymptotically by rejecting the time delay. To begin with, by rewriting the target system in a connecting form, a subsystem which is affected by the time-delay states of other nodes is established. And then, for this subsystem, a distributed observer with time delay is constructed. Moreover, an equivalent state transformation is made for the observer error dynamic system based on the observable canonic decomposition theorem. Further, in order to ensure that the distributed observer error dynamic system is asymptotically stable even if there exists a time delay, a linear matrix inequality (LMI) which is relative to the Laplace matrix is elaborately set up, and a special Lyapunov function candidate based on the LMI is considered. Next, based on the Lyapunov function and Lyapunov stability theory, we prove that the error dynamic system of the distributed observer is asymptotically stable, and the observer gain is determined by a feasible solution of the LMI. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

The effect of path curvature on the stability of reversing truck–semitrailer in the presence of feedback delay

Stability analysis of the low-speed reverse motion along clothoid curve is presented for the truck–semitrailer combination. The single-track kinematic model supplemented with the steering system and the lower-level controller is applied. A higher-level controller is designed to stabilise the reverse motion of the vehicle. Linear state feedback with time delay is used with feedforward term to force the vehicle to the desired path. The linear stability analysis is done by semi-discretization and D-subdivision methods to determine the optimal control gain setup. The effects of path curvature and time delay on the stability are investigated and verified via numerical simulations. Results are validated via experiments using a small-scale test rig.

Design of a resilient wide-area damping controller using time delays

Design of a resilient wide-area damping controller using time delays

An Intelligent Transport System Using Vehicular Network for Smart Cities

Aims and background: The integration of communication tools has allowed for effective decision-making in smart cities and Internet-of-Things (IoT). One major issue that people who commute to cities everyday encounter is traffic congestion. Thanks to the progress and backing of ICTs, transportation solutions have been designed and implemented, leading to the development of ITSs and the provision of numerous innovative services. Objectives and Methods: These services include ones that guarantee safety, provide drivers with useful information, enable greater street movement, and avoid congestion, among many others. In industrialized nations, traffic data is collected by specialized sensors that can anticipate future patterns. Commuters are kept informed of any traffic updates through the Internet. When there is little or no physical infrastructure and Internet connection, these methods become unworkable. Internet access is still a problem in rural regions, and there are no roadside units in underdeveloped nations. This article presents an architecture for smart cities' intelligent vehicular networks that can impromptu accept data from nearby vehicles in real time and use it to choose routes. As embedded devices in vehicles, we utilized Android-based smartphones with Wi-Fi Direct capabilities. To set up our smart transportation system, we utilized a vehicular ad hoc network. Results: Data was collected and processed using separate methods between two major cities in a developing nation. Resource utilization, transmission delay, packet loss, and total trip time were measured against several fixed- and dynamic-route-selection algorithms to assess the framework's performance. Conclusions: When equated to a conventional fixed-route-selection procedure, our results reveal a 33.3% reduction in trip times.

Modeling of drinking and driving behaviors among adolescents and young adults in the United States: Complexities and Intervention outcomes

Alcohol-impaired driving is a formidable public health problem in the United States, claiming the lives of 37 individuals daily in alcohol-related crashes. Alcohol-impaired driving is affected by a multitude of interconnected factors, coupled with long delays between stakeholders’ actions and their impacts, which not only complicate policy-making but also increase the likelihood of unintended consequences. We developed a system dynamics simulation model of drinking and driving behaviors among adolescents and young adults. This was achieved through group model building sessions with a team of multidisciplinary subject matter experts, and a focused literature review. The model was calibrated with data series from multiple sources and replicated the historical trends for male and female individuals aged 15 to 24 from 1982 to 2020. We simulated the model under different scenarios to examine the impact of a wide range of interventions on alcohol-related crash fatalities. We found that interventions vary in terms of their effectiveness in reducing alcohol-related crash fatalities. In addition, although some interventions reduce alcohol-related crash fatalities, some may increase the number of drinkers who drive after drinking. Based on insights from simulation experiments, we combined three interventions and found that the combined strategy may reduce alcohol-related crash fatalities significantly without increasing the number of alcohol-impaired drivers on US roads. Nevertheless, related fatalities plateau over time despite the combined interventions, underscoring the need for new interventions for a sustained decline in alcohol-related crash deaths beyond a few decades. Finally, through model calibration we estimated time delays between actions and their consequences in the system which provide insights for policymakers and activists when designing strategies to reduce alcohol-related crash fatalities.

Carbon Offsets and Concerns About Shifting Harms: A Reply to Elson

Luke Elson defends carbon offsetting on the basis that it is not morally objectionable to shift harms or risks around. As long as emitting and offsetting does not increase the overall harms or risks—and merely shifts them—compared to refraining from emitting, he suggests there is no injustice involved. I respond in several ways, suggesting that the time delay involved in offsetting can increase these risks but, regardless, there is a defensible default which could justify refraining from emitting, even when planning to offset.

Measurements of ignition delay time of gas-to-liquid (GTL) fuel blends

The ignition delay time (IDT) is a fundamental combustion parameter of any fuel, which has a direct impact on its combustion and exhaust emissions in diesel engines. In this research, a thorough experimental study was conducted to investigate the ignition delay of Gas-to-Liquid (GTL) fuel and its 50%–50 % blends with diesel under a wide range of operating conditions using a conventional shock tube apparatus. Simultaneously, a comprehensive chemical kinetic model, based on the well-established POLIMI mechanism, was developed to simulate the complex combustion chemistry of diesel, GTL, and their blends. Several loading pressures in the driver section ranging from 6 to 14 bar that results in reflected pressure of 8–16 bar, and equivalence ratios ranging from 0.5 to 1.3 as well as different initial temperatures have been examined. Calibration of the shock tube indicated that a driver gas tailoring technique was necessary to be used, which was conducted by adding a small ratio of either argon or nitrogen to helium to get an extended test time by 32 % with a good rapture pressure. IDT measurements showed that GTL has the shorter ignition delay time than that of diesel fuel for all conditions. The findings show that IDT measurements for GTL fuel has a shorter ignition delay time than that of diesel fuel for all conditions. Under stoichiometric conditions (ɸ = 1.0), IDT of the blended fuel was about 3 ms, very close to that of GTL at 975 K. However, at a temperature above 1000 K, the IDT of the three fuels were almost identical and ranging between 1 and 2 ms. At a temperature of 1100 K, the IDT of the blended fuel was 5.5 ms, almost a middle value between those of the pure diesel, 0.522 ms, and GTL fuel, 0.495 ms. The shortest IDT of the blended fuel was about 0.4 ms with the highest value of the reflected pressure of 14 bar, while the longest IDT was around 10 ms with the rich mixture at ɸ = 1.3. The study can add to the existing literature illustrating the behavior of GTL-diesel blend can affect IDT.

Sensitive determination of Gabapentin in plasma sample using dispersive liquid-liquid microextraction coupled with ion mobility spectrometry

Gabapentin (GBP) is an anticonvulsant agent and its determination using a fast and simple method is challenging. In this research, a novel sensitive, and economical method for the fast determination of GBP in biological samples was developed. This method benefits from the advantages of ion mobility spectrometry (IMS) as a fast detection and separation system and dispersive liquid-liquid microextraction (DLLME) for the preconcentration/extraction of GBP. In the developed method (DLLME-IMS), Ag nanoparticles serve as modifiers. Moreover, the quantum theory of atoms in molecules (QTAIM) analysis was employed to investigate the interaction mechanism between GBP and Ag nanoparticles. Also, a delay time after the injection of the sample was applied to improve the method sensitivity. Under the optimum condition, the developed method showed a linear response over the concentration range of 0.3–12 μg mL−1 and a detection limit of 0.12 μg mL−1. Eventually, DLLME-IMS was successfully employed in plasma sample, and was validated against the HPLC method with UV detection as a reference method. The developed method will open up a new avenue for the development of effective, rapid, and simple analytical methods.