Instantaneous Drop Research Articles

Seismic performance and recovery of medical infrastructure in Mexico City related to the September 19, 1985 and 2017 earthquakes

To date, the September 19, 1985 Michoacán (Ms = 8.1) and the September 19, 2017 Puebla-Morelos (Mw = 7.1) earthquakes have been the most devastating seismic events in Mexico City. During the 1985 earthquake, 13 important public hospital buildings collapsed or were demolished and 5800 hospital beds were lost. During the 2017 earthquake, 85 buildings of the medical sector were disturbed, two major public hospital were demolished and 1147 hospital beds were affected. In this paper, the author concentrates both in reviewing what occurred during the 1985 earthquake, and in reporting what it has been observed for the 2017 earthquake. From the structural viewpoint, the observed damage is discussed in relationships to: a) seismic codes, b) spectral demands, b) structural irregularities, c) soil settlements, d) tilting, e) structural pounding and, f) deterioration. The observed damaged inventory is also put into perspective with respect to the approximate number of medical facilities that are available in Mexico City. An instantaneous drop of seismic resilience for this sector is crudely assessed. Finally, the progress on the recovery process or adaptive resilience is discussed. Fortunately, most of the main hospitals in Mexico City were not severely damaged, and that it was why most of them and the hospital bed capacity in Mexico City previous to the 2017 earthquake was able to be recovered on time to attend the Covid-19 pandemic which affected Mexico since early 2020.

Pressure Source Model of the Production Process of Natural Gas from Unconventional Reservoirs

This work is focused on developing a computational model to predict the production rate and pressure evolution of natural gas from unconventional reservoirs, particularly shale gas deposits. The model is based on the principle of conservation of mechanical energy and was developed from the transient solution of Bernoulli’s equation. This solution was obtained by computing the pressure evolution in the well resulting from the combined action of extracting the free gas and of gasification from kerogen. The transient behavior of gas production by hydraulic fracturing was calculated by numerically integrating Bernoulli’s equation. The curves representing gas flow evolution were considered as a series of stepwise steady states under a constant gas flow rate, similar to the pressure–time curves. These time steps were connected by instantaneous drops in pressure or gas flow rates. On the other hand, the delayed release of the adsorbed and dissolved gas in the kerogen was accurately calculated by introducing a semi-empirical gas pressure source term into the gas well pressure equation. The effect of this source is to gradually increase the gas pressure in the reservoir, emulating the gas release mechanisms from the organic matter. Model validation was based on production data from the unconventional reservoirs Eagle Ford, U.S.A., and Burgos basin, México. The initial measured gas production rate was used to determine a global friction factor of the gas flowing out from soil cracks and ducts. Additionally, measured production rate data were used to determine the coefficients of the source term function. Pearson correlation coefficients of 0.97 and 0.96 were obtained for Eagle Ford and Burgos basins data, respectively. In contrast, the corresponding coefficients calculated from the traditional Arps’ model were 0.89 and 0.5, respectively. The present pressure source model (PSM) represents a new approach to characterize the process of gas production from unconventional reservoirs, proving to be accurate in forecasting both the gas flow rate and pressure evolution during gas production. The postulated pressure source term was shown to mimic the desorption and diffusion kinetics, which release free gas from the kerogen.

A physics-informed machine learning model for the prediction of drop breakup in two-phase flows

Predictive simulations of two-phase flows are highly sought after because of their widespread applications in propulsion, energy, agriculture, and medicine. One crucial goal for many of these simulations is the accurate and efficient prediction of the size distribution and number density of atomized drops. The multi-scale nature of these flows makes it practically impossible to capture all scales within a single simulation. In particular, the breakup processes producing the smallest drops through secondary breakup often necessitate resolutions far below the Kolmogorov scale. Consequently, models must be employed for secondary breakup. Existing physics-based and stochastic breakup models are not universal and fail to account for the local and instantaneous flow field and drop geometry. We present a physics-informed machine learning model for predicting the statistics of daughter drops generated during the breakup of under-resolved drops. By training on high-fidelity simulations, the model can predict breakup outcomes from severely under-resolved input fields. This is made possible by a careful choice of quantities of interest and by taking inspiration from the discrete nature of breakup events to encode the temporal evolution via a mixture of sigmoid functions. We showcase proof-of-concept results from the canonical settings of 3D Taylor–Green vortex flows and homogeneous isotropic turbulence. Compared to results generated by low-resolution simulations (i.e., without a model) and baseline state-of-the-art models, our approach achieves superior accuracy in predicting drop size distribution and critical quantities of interest, such as surface area. This work paves the path towards the development of embedded machine learning models for the prediction of primary and secondary breakup.

A Study on the Time-Frequency Characteristics of Electromagnetic Radiation Signals during Concrete Cracking

At the moment of rupture, brittle materials such as concrete, coal, and rocks experience a sudden stress change that generates oscillating positive and negative charges on the crack surfaces, resulting in the emission of electromagnetic radiation (EMR) signals. While extensive investigations have focused on the EMR signals produced during the fracturing of coal and rocks, limited attention has been given to the signals arising from concrete cracking. Previous studies have predominantly concentrated on amplitude or frequency domain analysis, lacking a comprehensive exploration of the time-frequency domain characteristics of electromagnetic signals. In this study, various magnetic field sensors capable of collecting frequencies ranging from 50Hz to 50kHz are developed. A laboratory testing platform for concrete cracking is established with the utilization of data acquisition equipment and a rock point load tester. The EMR signals are subjected to time-frequency domain analysis using Short-Time Fourier Transform (STFT) methods. The study explores the relationship between the time-frequency domain characteristics of EMR signals and concrete dimensions, as well as the instantaneous stress drop at the moment of fracture. Experimental findings reveal that the dominant frequency of EMR signals generated during concrete cracking is in the low-frequency range. As the instantaneous stress drop at the moment of fracture increases, the frequency of the EMR signals shifts towards higher frequencies and the signals around 10kHz has a longer duration. When the frequency of EMR signals is lower than 20kHz, larger concrete dimensions result in greater stress drops at the moment of fracture, leading to higher intensity EMR signals. Utilizing the EMR characteristics of concrete cracking holds promise for monitoring the safety and stability of concrete structures.

Data-driven modeling of the aerodynamic deformation and drag for a freely moving drop in the sub-critical Weber number regime

Accurate prediction of the dynamics and deformation of freely moving drops is crucial for numerous droplet applications. When the Weber number is finite but below a critical value, the drop deviates from its spherical shape and deforms as it is accelerated by the gas stream. Since aerodynamic drag on the drop depends on its shape oscillation, accurately modeling the drop shape evolution is essential for predicting the drop’s velocity and position. In this study, 2D axisymmetric interface-resolved simulations were performed to provide a comprehensive dataset for developing a data-driven model. Parametric simulations were conducted by systematically varying the drop diameter and free-stream velocity, achieving wide ranges of Weber and Reynolds numbers. The instantaneous drop shapes obtained in simulations are characterized by spherical harmonics. Temporal data of the drag and modal coefficients are collected from the simulation data to train a Nonlinear Auto-Regressive models with eXogenous inputs (NARX) neural network model. The overall model consists of two multi-layer perceptron networks, which predict the modal coefficients and the drop drag, respectively. The drop shape can be reconstructed with the predicted modal coefficients. The model predictions are validated against the simulation data in the testing set, showing excellent agreement for the evolutions of both the drop shape and drag.

Iron Active Center Coordination Reconstruction in Iron Carbide Modified on Porous Carbon for Superior Overall Water Splitting.

In this work, a novel liquid nitrogen quenching strategy is engineered to fulfill iron active center coordination reconstruction within iron carbide (Fe3C) modified on biomass-derived nitrogen-doped porous carbon (NC) for initiating rapid hydrogen and oxygen evolution, where the chrysanthemum tea (elm seeds, corn leaves, and shaddock peel, etc.) is treated as biomass carbon source within Fe3C and NC. Moreover, the original thermodynamic stability is changed through the corresponding force generated by liquid nitrogen quenching and the phase transformation is induced with rich carbon vacancies with the increasing instantaneous temperature drop amplitude. Noteworthy, the optimizing intermediate absorption/desorption is achieved by new phases, Fe coordination, and carbon vacancies. The Fe3C/NC-550 (550 refers to quenching temperature) demonstrates outstanding overpotential for hydrogen evolution reaction (26.3mV at -10 mAcm-2) and oxygen evolution reaction (281.4 mV at 10mAcm-2), favorable overall water splitting activity (1.57 V at 10 mAcm-2). Density functional theory (DFT) calculations further confirm that liquid nitrogen quenching treatment can enhance the intrinsic electrocatalytic activity efficiently by optimizing the adsorption free energy of reaction intermediates. Overall, the above results authenticate that liquid nitrogen quenching strategy open up new possibilities for obtaining highly active electrocatalysts for the new generation of green energy conversion systems.

Effect of Heating Surface Geometry on the Droplets Evaporation under Leidenfrost Conditions

Physical and geometric factors are generally regarded as the main cause of evaporation characteristics of the Leidenfrost droplets levitating above the hot surface. It is well-known and generally accepted that similar research is conducted under different conditions and on individual measurement set-ups. This is one of the potential reasons for the differences in the results of thermal fluxes and computational models in scientific papers. This paper discusses the influence of the heating surface geometry on the heat transfer coefficient h during water drops evaporation under film boiling regime. The variable geometry parameters are the curvature radius of the heating bowl of R = 64 and 254 mm. Individually compiled test stands made it possible to measure the instantaneous drop mass for each R radius and to determine the coefficient h. The methodology was validated by calculating the relative error. It changes with the curvature radius and the droplet size, and for droplet mass from about 2 g to 0.3 g does not exceed ±10%. The heat transfer coefficient h is about 15% higher for a drop located on a surface with a larger radius of curvature. Moreover, the method that was devised allows us to estimate the h value for asymmetric droplet shapes. The advantage of the adopted method of measuring the drop mass over time is the possibility of analyzing heat transfer processes in any drop shape range, even in the case of asymmetric ones. Previous research methods were mainly based on determining the mass of the drop by calculating its volume.

Highly Reliable Short-Circuit Protection Circuits for Gallium Nitride High-Electron-Mobility Transistors

This paper presents a circuit for detecting and protecting against short circuits in E-mode gallium nitride high-electron-mobility transistors (GaN HEMTs) and analyzes the protection performance of the circuit. GaN HEMTs possess fast switching characteristics that enable high efficiency and power density in power conversion devices. However, these characteristics also pose challenges in protecting against short circuits and overcurrent situations. The proposed method detects short-circuit events by monitoring an instantaneous drop in the DC bus voltage of a circuit with GaN HEMTs applied and uses a bandpass filter to prevent the malfunction of the short-circuit protection circuit during normal switching and ensure highly reliable operation. Using this method, the short-circuit detection time of E-mode GaN HEMTs can be reduced to 257 ns, successfully protecting the device without malfunctions even in severe short-circuit situations occurring at high DC link voltages.

Current Interrupt Technique to Fully Characterize PEMWE Cells

It is common practice to characterize cells in polymer electrolyte membrane water electrolysis (PEMWE) using electrochemical impedance spectroscopy (EIS) and Tafel analysis, which require special equipment and operation procedures. Additionally, these techniques are not suitable for large industrial size cells with very low impedances. We present a simpler approach based on a novel evaluation of the current interrupt (CI) technique. The CI technique utilizes the voltage response after an instantaneous drop of electric current to identify the ohmic resistance R Ω, charge transfer resistance R ct and double-layer capacity C dl in a simplified equivalent circuit (EC) of the cell. A direct link to results of typical EIS and Tafel analysis can be defined by using the improved CI method which considers a non-linear activation resistance instead of a constant charge transfer resistance. Thereby, access to equivalent information as the established standard method is granted, while being applicable to all cell and stack sizes without requiring special equipment (e.g. impedance spectrometer). The agreement with experimental data is significantly improved over the assumption of a constant charge transfer coefficient. Consistency of the proposed interpretation with explicit EIS and Tafel analysis is demonstrated and options for industrial application of the evaluation scheme are discussed.

Inelastic effects in bulge formation of inflated polymer tubes.

When a soft tube is inflated, it may sometimes show a bulge instability wherein a portion of the tube inflates much more than the rest. The bulge instability is well-understood for hyperelastic materials. We examine inflation of polyurethane tubes whose material behavior is not strictly hyperelastic. Upon inflating at constant rate, the tubes deform into a variety of shapes including irregular axisymmetric shapes with multiple localized bulges, a single axially-propagating bulge, or homogeneous cylindrical shapes. In all cases regardless of the inflation mode, the pressure first rises to a maximum, and then gradually reduces towards a plateau. We document numerous differences as compared to hyperelastic tubes. Most notably a pressure maximum can appear even without bulging, whereas for hyperelastic tubes, a pressure maximum is necessarily accompanied by bulging. Further, the decrease in pressure beyond the maximum occurs gradually over timescales as long as an hour, whereas bulging of hyperelastic tubes induces an instantaneous drop in pressure. We also observe permanent deformation upon deflation, a decrease in the pressure maximum during a subsequent second inflation, and more severe bulge localization at low inflation rates. Existing theory of hyperelastic tube inflation cannot capture the observed behaviors, even qualitatively. Finite element simulations suggest that many of the observations can be explained by viscoelasticity, specifically that a slow material response allows the pressure to remain high for long durations, which in turn allows growth of multiple bulges.

Numerical simulation study on heat transfer and fluid performance of novel calcium carbide heat collection system

This article proposes a novel recovery system for the substantial waste heat from the hot calcium carbide (CA). The study employs numerical simulation to investigate the heat transfer performance of the heat collection system (HCS). The research explores the effects of outlet position, inlet velocity, and inlet temperature on the operational characteristics and heat transfer performance of the HCS. The results indicate that optimal heat transfer performance is achieved when the outlet position is at the center of the collector. Instantaneous efficiency (IE), exergy loss (EL), pressure drop (PD), and heat transfer coefficient (HTC) increase with the velocity, while effectiveness decreases with the velocity. The peak values for IE, effectiveness, and HTC are 28.22%, 29.69%, and 1212.45 W/(m2*K), respectively. The heat transfer performance of the HCS is highest when the inlet temperature is 280K. The proposed CA HCS holds significant importance for recovering waste heat from electric stone production, providing a theoretical basis for subsequent experimental work.

The impact of the national volume-based procurement policy on the use of policy-related drugs in Nanjing: an interrupted time-series analysis

BackgroundIn September 2019, the “4 + 7” centralized procurement pilot program was expanded nationwide aiming at reducing drug prices by means of volume-based procurement and using accredited generic drugs for branded drug substitutes. Given the current uncertain effect of the policy outside pilot areas, this study was conducted to evaluate the impact of the National Volume-based Procurement policy on the use of policy-related drugs after expansion.MethodA single-group interrupted time series was applied using drug purchase data, covering 25 months from December 2018 to December 2020. Drugs related to the centralized procurement policy were selected as samples, including 25 first-batch policy-related drugs and 56 alternative drugs. Centralized procured drugs can be divided into bid-winning and non-winning products, where non-winning products were sorted into generic and branded drugs, and alternative products were classified according to different degrees of substitution. Purchase volume, expenditures, and daily costs were measured.ResultsAfter the implementation of the policy, a significant increase was associated with the volume of bid-winning drugs (p < 0.001) and the volume of generic and branded drugs decreased immediately. The DDDc of drugs under the same generic name significantly reduced (an instantaneous drop of bid-winning drugs by approximately 25%, 7.62 CNY for generics and 3.07 CNY for branded drugs), saving 48.2 million CNY of drug expenditures. The policy has a significant effect on the drug for the treatment of cardiovascular diseases and exerted little influence on the drug for the treatment of nervous diseases, and the substitution of generics for antitumor-branded drugs was not obvious. In addition, the procurement volume of alternative drugs appeared to be a “carry-over”.ConclusionsThese findings indicated that the policy demonstrated positive effects in terms of price reductions and cost savings and accelerated the substitution of generics against branded drugs. The “patent cliff” for branded drugs has gradually emerged. Besides, a short-term “spillover effect” of the volume of alternative drugs was observed, requiring special attention and vigilance.

Decoupling electroplasticity by temporal coordination design of pulse current loading and straining

Multi-mechanism coupled electroplasticity (EP) has not been fully elucidated yet due to the difficulty in eliminating thermal effect, although isothermal, air-cooled, and cryogenic methods are usually used, there are different heating histories from electrically-assisted deformation. The 0–7% pre-strained Ti–6Al–4V alloy is taken as the case material. Based on the two different characteristics of the time-accumulation of thermal effect and the instantaneous nature of the athermal effect, a comparative study is conducted by designing two temporal coordination methods of pulse current and straining, viz., asynchronous loading with high-energy current (ALHC) and synchronous loading with low-energy current (SLLC), where the thermal and athermal effects are highlighted by different loading times, loading and unloading moments of pulse current of different magnitudes. Under ALHC condition, the decreasing yield strength and increasing elongation of the 7% pre-deformed material are observed with increasing current density and loading times, and stress reduction up to 20.7% for yield strength and ductility recovery of maximal 99.1% for elongation are obtained for 14.0 A/mm2 and loading three times. Moreover, stage B of the work hardening rate related to dislocation de-pinning disappears, and the TEM shows an annealing effect that the tangled dislocations are annihilated and rearranged by climbing. Thus, the Joule heat-based thermal effect dominates this condition. Under SLLC condition, the loading and unloading of pulse current of 2.81 A/mm2 in the plastic stage result in an instantaneous drop and rebound in flow stress and work hardening rate (stage B exists), respectively, and are accompanied by the negligible instantaneous temperature rise, while loading at the elastic stage, the overall flow stress and work hardening rate is decreased. It is concluded that the athermal effect can lower the dislocation phonon drag effect and the deformation activation energy, and change the athermal atomic state and dislocation slip mode, which dominates the varied flow stress and elongation. A dislocation dynamics-based physical model is developed by taking into account phonon drag, diffusion activation energy, and deformation activation energy to account for the thermal and athermal effects on dislocations, providing a self-consistent explanation of the above behaviors and mechanisms of the flow stress and ductility under ALHC and SLLC conditions.

Macroscale simulation of particle loading in electrostatically charged filters

Existing studies have shown that particle collection efficiency of a charged filter tends to decrease with particle loading to a certain extent, then increase with further loading. This contrasts with pressure drop which monotonically increases with particle loading. This trend in particle collection efficiency is due to a variety of factors including, but not limited to, neutralization and aerodynamic shielding of the fibers' electrostatic field. The current paper presents a semi-empirical macroscale simulation method to predict the instantaneous pressure drop and particle collection efficiency of an electrostatically charged filter during the early stages of particle loading. The simulations were performed by using ANSYS software enhanced with a series of in-house subroutines. The simulation results are compared with experimental data (for calibration and validation) obtained from testing a bipolarly-charged (55 μC m−2) polypropylene filter exposed to different levels of nanoparticle loadings. The filter media was loaded (both experimentally and computationally) with polydisperse NaCl nanoparticles (count median diameter of 75 nm) having charge values of ±1e. The loaded media were then tested (experimentally and computationally) with NaCl nanoparticles spanning 10 nm–500 nm in electrical mobility diameter (from TSI 3160 filter tester) having a Fuchs charge distribution. In addition, a high-porosity conditional factor was developed for the Kozeny-Carman permeability equation to expand its application to the case of nanoparticle deposits, where the dendrites’ porosity is very high, and aerodynamic slip is expected to occur.

Macroscale modeling of electrostatically charged facemasks

In this study, the instantaneous collection efficiency and pressure drop of an N95 facemask is numerically simulated in a setting similar (but not identical) to that used by NIOSH to certify N95 respirators. More specifically, a CPU-friendly macroscale model is developed, for the first time, to simulate the performance of an electrostatically-charged facemask when the mask is clean and when it is loaded with neutral or neutralized nanoparticles. The simulations were performed using ANSYS software enhanced with in-house subroutines, and they were calibrated using the experimental data reported by Balazy et al. (2006) for the initial efficiency of N95 masks. In addition, a correction factor was developed for the Kozeny-Carman permeability equation to expand its application to the case of nanoparticle-deposits, where the dendrites porosity is very high and the aerodynamic slip is expected to occur.

開極タイミング変化時におけるアーク温度の解析

The gas circuit breakers have the problem of re-ignition after current zero. The instantaneous voltage drop causes enormous damage in the case of current interruption failure. Therefore, it is the responsibility of circuit breaker to interrupt the current quickly and reliably. Efficient cooling of the arc temperature is important in order to prevent the re-ignition caused by the transient recovery voltage. In this paper, the arc temperature as a function of opening electrodes timing was analyzed. As a result, the three-dimensional transition of arc temperature to current zero for each current interruption timing at each sine wave time was obtained. In addition, the opening electrodes timing that decreases the arc conductance at current zero was elucidated.

Mouse Model of Spinal Cord Hypoperfusion with Immediate Paralysis Caused by Endovascular Repair of Thoracic Aortic Aneurysm.

A clinically relevant mouse model of thoracic endovascular aortic repair-induced ischemic spinal cord injury has been lacking since the procedure was first employed in 1991. The hypothesis was that ligation of mouse intercostal arteries would simulate thoracic endovascular aortic repair-induced ischemic spinal cord injury and behavioral deficit. The aim was to create a mouse model of thoracic endovascular aortic repair-induced spinal cord hypoperfusion by ligating five pairs of mouse intercostal vessels. Mice were divided into sham (n = 53) and ligation (n = 60) groups. The procedures called for double ligation of three pairs and single ligation of two pairs of thoracic intercostal arteries in adult C57BL/6 mice. A laser Doppler probe was used in vivo on the spinal cords and intercostal arteries to document the extent of arterial ligation and spinal cord hypoperfusion. The Basso Mouse Scale for Locomotion, histological studies, and electron microscopy demonstrated postligation locomotive and histopathological changes. Ligation induced a significant and instantaneous drop in blood flow in the intercostal arteries (% change; mean = -63.81; 95% CI, -72.28 to -55.34) and the thoracic spinal cord (% change; mean = -68.55; 95% CI, -80.23 to -56.87). Paralysis onset was immediate and of varying degree, with behavioral deficit stratified into three groups: 9.4% exhibited severe paralysis, 37.5% moderate paralysis, and 53.1% mild paralysis at day 1 (n = 32; P < 0.001). Mild and moderate paralysis was transient, gradually improving over time. Severe paralysis showed no improvement and exhibited a higher mortality rate (83%; n = 15 of 18) compared to moderately (33%; n = 6 of 18) and mildly (24%; n = 6 of 25) paralyzed mice (P < 0.001). The overall ligation group survival rate (84%; n = 46 of 55) was significantly lower than the sham group (100%; n = 48 of 48) with P = 0.003. The mouse model generates reproducible spinal cord hypoperfusion and accompanying histopathological ischemic spinal cord damage. The resulting anatomical changes and variable behavioral deficits mimic the variability in radiological and clinical findings in human patients.

Aqueous extraction of anthocyanin from hibiscus by coupling instantaneous pressure drop and microwave assisted process

This paper discusses about the optimization of process parameters for the extraction of anthocyanin from Hibiscus rosa-sinensis by instantaneous pressure drop pre- treatment and microwave assisted extraction process using water as solvent. The experimental design was formulated with the help of response surface methodology (RSM). The process parameters viz., process pressure, treatment time, microwave power and solvent to sample ratio were optimized based on the yield of anthocynine content. The maximum yield of anthocyanin was obtained with the treatment combination of 1.12 kg/cm2 process pressure, 2 min treatment time, 960 W microwave powers, 27.5 solvent to sample ratio. Conventional aqueous extraction of anthocyanin resulted in less yield (Cold extraction- 85 mg/L, Hot extraction- 93.5 mg/L). The conventional method was found to be time consuming compared to coupled system which will take few minutes.

Development and assessment of a particle tracking velocimetry (PTV) measurement technique for the experimental investigation of oil drops behaviour in dispersed oil–water two-phase flow within a centrifugal pump impeller

The objective of the current work is to present the development of a Particle Tracking Velocimetry (PTV) algorithm for the analysis of oil drops behaviour in two-phase oil–water dispersions within a centrifugal pump impeller. The drop tracking was realized through high-speed camera images in a transparent pump prototype, which enabled the visualization of oil drops dispersed in water in all the impeller channels. The PTV algorithm is based on deep-learning techniques for image processing. The drops are detected by a combined U-Net and Convolutional Neural Network (CNN) method, with the former generating a binary image and the latter detecting valid oil drop contours. After detection, the Labelled Object Velocimetry (LOV) is adopted to calculate the instantaneous oil drop velocity. A synthetic image generator based on a Generative Adversarial Network (GAN) is then developed to assess the results from the U-Net, CNN, and LOV models. Additional validation studies are performed using the results from Perissinotto et al. (2019a). The results reveal that the presented deep-learning PTV algorithm is robust and provides consistent and reliable data for the dispersed oil phase in two-phase oil–water flows.

False actions of the aviation fire protection system caused by disturbances in power circuits

Abstract The article presents the results of simulation tests of the SSP-FK aviation fire protection system and the identification of the main causes of its false operation on many airplanes and helicopters of the Polish Armed Forces with the use of a diagnostic simulator built at ITWL. The results of the performed statistical analyzes pointing to the execution blocks as the key factors in false fire signaling are discussed. Selected test results of the developed simulation model of the actuator unit under the conditions of disturbances occurring in its supply circuits (in particular instantaneous voltage drops) are presented. The effectiveness of the presented test method with the use of a simulation model of a fire protection system, which can be used to train the engineering and aviation service and pilots, and to support the work of the Aircraft Accident Investigation Commission, was pointed out.