THE ANALYSIS OF ELECTROMAGNETIC PROCESSES IN OUTPUT CIRCUIT OF THE GENERATOR OF DISCHARGE PULSES WITH NON-LINEAR MODEL OF PLASMA-EROSIVE LOAD AT CHANGE THEIR PARAMETERS IN WIDE RANGES

This paper reports on the study of microporous polydimethylsiloxane (PDMS) foams as a highly deformable dielectric material used in the composition of flexible capacitive pressure sensors dedicated to wearable use. A fabrication process allowing the porosity of the foams to be adjusted was proposed and the fabricated foams were characterized. Then, elementary capacitive pressure sensors (15 × 15 mm2 square shaped electrodes) were elaborated with fabricated foams (5 mm or 10 mm thick) and were electromechanically characterized. Since the sensor responses under load are strongly non-linear, a behavioral non-linear model (first order exponential) was proposed, adjusted to the experimental data, and used to objectively estimate the sensor performances in terms of sensitivity and measurement range. The main conclusions of this study are that the porosity of the PDMS foams can be adjusted through the sugar:PDMS volume ratio and the size of sugar crystals used to fabricate the foams. Additionally, the porosity of the foams significantly modified the sensor performances. Indeed, compared to bulk PDMS sensors of the same size, the sensitivity of porous PDMS sensors could be multiplied by a factor up to 100 (the sensitivity is 0.14 %.kPa−1 for a bulk PDMS sensor and up to 13.7 %.kPa−1 for a porous PDMS sensor of the same dimensions), while the measurement range was reduced from a factor of 2 to 3 (from 594 kPa for a bulk PDMS sensor down to between 255 and 177 kPa for a PDMS foam sensor of the same dimensions, according to the porosity). This study opens the way to the design and fabrication of wearable flexible pressure sensors with adjustable performances through the control of the porosity of the fabricated PDMS foams.

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Analysis of Single Buffer Random Polling System With State-Dependent Input Process and Server/Station Breakdowns

International Journal of Operations Research and Information Systems ◽

10.4018/ijoris.2018010102 ◽

2018 ◽

Vol 9 (1) ◽

pp. 22-50 ◽

Cited By ~ 2

Author(s):

Thomas Y.S. Lee

Keyword(s):

Steady State ◽

Linear Model ◽

Repair Process ◽

Polling System ◽

Steady State Analysis ◽

Relaxation System ◽

Polling Model ◽

State Dependent ◽

Non Linear ◽

State Analysis

Models and analytical techniques are developed to evaluate the performance of two variations of single buffers (conventional and buffer relaxation system) multiple queues system. In the conventional system, each queue can have at most one customer at any time and newly arriving customers find the buffer full are lost. In the buffer relaxation system, the queue being served may have two customers, while each of the other queues may have at most one customer. Thomas Y.S. Lee developed a state-dependent non-linear model of uncertainty for analyzing a random polling system with server breakdown/repair, multi-phase service, correlated input processes, and single buffers. The state-dependent non-linear model of uncertainty introduced in this paper allows us to incorporate correlated arrival processes where the customer arrival rate depends on the location of the server and/or the server's mode of operation into the polling model. The author allows the possibility that the server is unreliable. Specifically, when the server visits a queue, Lee assumes that the system is subject to two types of failures: queue-dependent, and general. General failures are observed upon server arrival at a queue. But there are two possibilities that a queue-dependent breakdown (if occurs) can be observed; (i) is observed immediately when it occurs and (ii) is observed only at the end of the current service. In both cases, a repair process is initiated immediately after the queue-dependent breakdown is observed. The author's model allows the possibility of the server breakdowns/repair process to be non-stationary in the number of breakdowns/repairs to reflect that breakdowns/repairs or customer processing may be progressively easier or harder, or that they follow a more general learning curve. Thomas Y.S. Lee will show that his model encompasses a variety of examples. He was able to perform both transient and steady state analysis. The steady state analysis allows us to compute several performance measures including the average customer waiting time, loss probability, throughput and mean cycle time.

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Analysis of a linear and non-linear model for diffusion–dispersion phenomena of pulp washing by using quintic Hermite interpolation polynomials

Afrika Matematika ◽

10.1007/s13370-021-00877-7 ◽

2021 ◽

Author(s):

Satinder Pal Kaur ◽

Ajay Kumar Mittal ◽

V. K. Kukreja ◽

Archna Kaundal ◽

N. Parumasur ◽

...

Keyword(s):

Linear Model ◽

Hermite Interpolation ◽

Non Linear ◽

Interpolation Polynomials ◽

Hermite Interpolation Polynomials

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Selection of models to describe the temperature-dependent development of Neoleucinodes elegantalis (Lepidoptera: Crambidae) and its application to predict the species voltinism under future climate conditions

Bulletin of Entomological Research ◽

10.1017/s0007485321000195 ◽

2021 ◽

pp. 1-9

Author(s):

Hevellyn Talissa dos Santos ◽

Cesar Augusto Marchioro

Keyword(s):

Climate Change ◽

Linear Model ◽

Future Climate ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Temperature Dependent ◽

Dependent Development ◽

Degree Day ◽

Non Linear ◽

The Impact

Abstract The small tomato borer, Neoleucinodes elegantalis (Guenée, 1854) is a multivoltine pest of tomato and other cultivated solanaceous plants. The knowledge on how N. elegantalis respond to temperature may help in the development of pest management strategies, and in the understanding of the effects of climate change on its voltinism. In this context, this study aimed to select models to describe the temperature-dependent development rate of N. elegantalis and apply the best models to evaluate the impacts of climate change on pest voltinism. Voltinism was estimated with the best fit non-linear model and the degree-day approach using future climate change scenarios representing intermediary and high greenhouse gas emission rates. Two out of the six models assessed showed a good fit to the observed data and accurately estimated the thermal thresholds of N. elegantalis. The degree-day and the non-linear model estimated more generations in the warmer regions and fewer generations in the colder areas, but differences of up to 41% between models were recorded mainly in the warmer regions. In general, both models predicted an increase in the voltinism of N. elegantalis in most of the study area, and this increase was more pronounced in the scenarios with high emission of greenhouse gases. The mathematical model (74.8%) and the location (9.8%) were the factors that mostly contributed to the observed variation in pest voltinism. Our findings highlight the impact of climate change on the voltinism of N. elegantalis and indicate that an increase in its population growth is expected in most regions of the study area.

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