Computational Issues Associated With Gear Rattle Analysis: Part II — Evaluation Criteria for Numerical Algorithms

1992 ◽  
Author(s):  
R. C. Barlow ◽  
C. Padmanabhan ◽  
Rajendra Singh
Keyword(s):  
Linear Model ◽  
Evaluation Criteria ◽  
Numerical Algorithms ◽  
Simulation Models ◽  
Physical Systems ◽  
Non Linear ◽  
Integration Algorithms ◽  
Domain Integration ◽  
Gear Rattle ◽  
Reliable Methods

Abstract The main focus of this study is to establish evaluation criteria for direct time domain integration algorithms used to solve gear rattle type problems. Such criteria may be used to identify specific numerical problems encountered. The ultimate goal obviously is to find reasonably accurate and reliable methods of solution for such physical systems. Six case studies of increasing complexity, linear to highly non-linear, are solved using well known algorithms. The solutions to the linear model are verified by using analytical results. Non-linear model solutions as yielded by different algorithms are compared qualitatively and quantitatively. Several non-linear simulation models have been validated by comparing predictions with experimental data and results available in the literature.

Computational Issues Associated with Gear Rattle Analysis

1995 ◽  
Vol 117 (1) ◽  
pp. 185-192 ◽  
Author(s):  
C. Padmanabhan ◽  
R. C. Barlow ◽  
T. E. Rook ◽  
R. Singh
Keyword(s):  
Mathematical Formulation ◽  
Evaluation Criteria ◽  
Numerical Algorithms ◽  
Order Reduction ◽  
Simulation Models ◽  
Reduction Gear ◽  
Contact Ratio ◽  
Model Order ◽  
Domain Integration ◽  
Gear Rattle

This paper proposes a new procedure for formulating the gear rattle type problem analytically before attempting a numerical solution. It also outlines appropriate evaluation criteria for direct time domain integration algorithms used to solve such problems. The procedure is necessary due to the non-analytical nature of the mathematical formulation describing vibro-impacts, which can lead to numerical “stiffness” problems. The method is essentially an “intelligent” pre-processing stage and is based on our experience in simulating such systems. Important concepts such as model order reduction, gear or clutch stiffness contact ratio, appropriate choice of non-dimensionalization parameters are illustrated through examples. Several case studies of increasing complexity are solved using various well known numerical algorithms; solutions are compared qualitatively and quantitatively using the proposed evaluation criteria, and specific numerical problems are identified. Some of the simulation models have also been validated by comparing predictions with experimental data.

Simulation-Models for the Phenological Development of Mythimna-Convecta (Walker) (Lepidoptera, Noctuidae)

1990 ◽  
Vol 38 (6) ◽  
pp. 649 ◽  
Author(s):  
G Mcdonald
Keyword(s):  
Linear Model ◽  
Simulation Models ◽  
Sine Wave ◽  
Linear Functions ◽  
Published Data ◽  
Field Development ◽  
Development Rates ◽  
Threshold Temperatures ◽  
Non Linear ◽  
Fluctuating Temperatures

Larvae of armyworm, Mythimna convecta, were reared under fluctuating temperatures (1-7-degrees; 3-13-degrees; 7-17-degrees; 11-24-degrees; 31-39-degrees-C). Data from these trials were combined with previsouly published data derived from constant-temperature studies (ranging from 15-degrees to 33-degrees-C) to model the effects of temperature on development rate. Temperature-dependent development rates for each of eight immature stages were described by one of three non-linear functions and by a linear model modified to improve the performance about the lower and upper temperature extremes. At the lower and upper thermal limits (< 11-degrees-C and > 33-degrees-C) of the species, survival of larvae under fluctuating temperatures was greater than recorded in previously published studies under equivalent constant temperatures. A serious constraint on fitting a model to the later larval instars was the inconsistent appearance of a seventh instar. The two sets of models were evaluated against field development in three winter and one summer experiments. The modified linear model, with capacity to manipulate predicted development at threshold temperatures, provided a marginally better prediction than did the non-linear model. The sine wave method for estimating diurnal temperatures from minimum and maximum temperatures was shown to produce overestimates of development rates. A correction factor for the seasonal conditions in western Victoria was provided.

scholarly journals Influence of the Porosity of Polymer Foams on the Performances of Capacitive Flexible Pressure Sensors

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1968 ◽  
Author(s):  
Sylvie Bilent ◽  
Thi Hong Nhung Dinh ◽  
Emile Martincic ◽  
Pierre-Yves Joubert
Keyword(s):  
Experimental Data ◽  
Linear Model ◽  
Dielectric Material ◽  
Pressure Sensors ◽  
Volume Ratio ◽  
Measurement Range ◽  
Polymer Foams ◽  
First Order ◽  
Non Linear ◽  
Flexible Pressure Sensors

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.

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

2018 ◽  
Vol 9 (1) ◽  
pp. 22-50 ◽  
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.

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

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.

Experimental demonstration of non-linear model-based in-line control of pH

1992 ◽  
Vol 2 (3) ◽  
pp. 145-153 ◽  
Author(s):  
Suhas K. Mahuli ◽  
R. Russell Rhinehart ◽  
James B. Riggs
Keyword(s):  
Linear Model ◽  
Experimental Demonstration ◽  
Model Based ◽  
Non Linear
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