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Abstract Since the early 1900s, repeated heat exposure has been used as a method to induce physiological adaptations that enhance our ability to tolerate heat stress during athletic and occupational pursuits. Much of this work has been dedicated to quantifying the time course of adaptation and identifying the minimum duration of acclimation required to optimise performance or enhance safety. To achieve this, investigators have typically applied classical (constant load) heat acclimation, whereby 60–90 min exercise is performed at the same absolute or relative intensity in a hot environment for 3–24 days, with adaptations evaluated using an identical forcing function test before and after. This approach has provided a foundation from which to develop our understanding of changes in thermoregulatory function, but it has several, frequently overlooked shortcomings, which have resulted in misconceptions concerning the time course of adaptation. It is frequently suggested that most of the thermoregulatory adaptations during heat acclimation occur within a week, but this is an oversimplification and a predictable artefact of the experimental designs used. Consequently, the time course of complete human adaptation to heat remains poorly understood and appears to vary considerably due to numerous individual factors. The purpose of this communication is to highlight the key methodological considerations required when interpreting the existing literature documenting adaptation over time. We also propose potential means by which to improve the way we induce and quantify the magnitude of adaptation to expedite discovery.

Since the early 1900s, repeated heat exposure has been used as a method to induce physiological adaptations that enhance our ability to tolerate heat stress during athletic and occupational pursuits. Much of this work has been dedicated to quantifying the time course of adaptation and identifying the minimum duration of acclimation required to optimise performance or enhance safety. To achieve this, investigators have typically applied classical (constant load) heat acclimation, whereby 60–90 min exercise is performed at the same absolute or relative intensity in a hot environment for 3–24 days, with adaptations evaluated using an identical forcing function test before and after. This approach has provided a foundation from which to develop our understanding of changes in thermoregulatory function, but it has several, frequently overlooked shortcomings, which have resulted in misconceptions concerning the time course of adaptation. It is frequently suggested that most of the thermoregulatory adaptations during heat acclimation occur within a week, but this is an oversimplification and a predictable artefact of the experimental designs used. Consequently, the time course of complete human adaptation to heat remains poorly understood and appears to vary considerably due to numerous individual factors. The purpose of this communication is to highlight the key methodological considerations required when interpreting the existing literature documenting adaptation over time. We also propose potential means by which to improve the way we induce and quantify the magnitude of adaptation to expedite discovery. [ABSTRACT FROM AUTHOR]

This study considers one of the partially accelerated life testing models, mainly a constant-stress approach with unified hybrid censored data. The data represents the lifetime of units following the exponentiated gamma distribution (EGD). The estimation techniques for the parameter of EGD and the acceleration factor are discussed, along with the maximum likelihood estimation technique, the Bayesian and E-Bayesian estimation. Utilizing the squared error loss (SEL) and LINEX loss functions, the E-Bayesian and Bayesian estimates are generated. For deriving the estimates of Bayesian and E-Bayesian approaches, we use the MCMC method. Real-world data is also provided for illustration. Furthermore, unified hybrid censoring schemes (HCSs) are examined to determine their effectiveness in the light of the results. In the end, we compare among the proposed methods during their findings. The study's findings demonstrate how well the suggested techniques work when utilizing unified HCS. The study also makes clear how important it is to adopt the CSPALT model, as it yields more failed things in a shorter amount of time than items with typical use situations. In conclusion, it is suggested that this research be used to tasks like industrial product reliability testing.

This study considers one of the partially accelerated life testing models, mainly a constant-stress approach with unified hybrid censored data. The data represents the lifetime of units following the exponentiated gamma distribution (EGD). The estimation techniques for the parameter of EGD and the acceleration factor are discussed, along with the maximum likelihood estimation technique, the Bayesian and E-Bayesian estimation. Utilizing the squared error loss (SEL) and LINEX loss functions, the E-Bayesian and Bayesian estimates are generated. For deriving the estimates of Bayesian and E-Bayesian approaches, we use the MCMC method. Real-world data is also provided for illustration. Furthermore, unified hybrid censoring schemes (HCSs) are examined to determine their effectiveness in the light of the results. In the end, we compare among the proposed methods during their findings. The study's findings demonstrate how well the suggested techniques work when utilizing unified HCS. The study also makes clear how important it is to adopt the CSPALT model, as it yields more failed things in a shorter amount of time than items with typical use situations. In conclusion, it is suggested that this research be used to tasks like industrial product reliability testing. [ABSTRACT FROM AUTHOR]

The accelerated life testing is the key methodology of evaluating product reliability rapidly. This paper presents statistical inference of Gompertz distribution based on unified hybrid censored data under constant-stress partially accelerated life test (CSPALT) model. We apply the stochastic expectation-maximization algorithm to estimate the CSPALT parameters and to reduce computational complexity. It is shown that the maximum likelihood estimates exist uniquely. Asymptotic confidence intervals and confidence intervals using bootstrap-p and bootstrap-t methods are constructed. Moreover the maximum product of spacing (MPS) and maximum a posteriori (MAP) estimates of the model parameters and accelerated factor are discussed. The performances of the various estimators of the CSPALT parameters are compared through the simulation study. In summary, the MAP estimates perform superior than MLEs (or MPSs) with respect to the smallest MSE values. [ABSTRACT FROM AUTHOR]

This paper is concerned with statistical inference of multiple constant-stress testing for progressive type-II censored data with binomial removal. The failure times of the test units are assumed to be independent and follow the modified Kies exponential (MKEx) distribution. The maximum likelihood method as well as Bayes method are used to derive both point and interval estimates of the parameters. Furthermore, a real data application for transformers turn insulation is used to illustrate the proposed methods. Moreover, this real data set is used to show that MKEx distribution can be a possible alternative model to the exponential, generalized exponential and Weibull distributions. Finally, simulation studies are carried out to investigate the accuracy of the different estimation methods.

In this paper, we describe how to analyze and propose the accelerated life test plans for the development of the excellence and reliability of the product. We focus on estimating the costs of maintenance service policy because it has a very significant position to assist any manufacturing organization for sale and available its equipment and maintenance cost-effective. The constant-stress partially accelerated life test is assumed when the lifetime of test units follows Generalized Inverted Exponential distribution under the progressive censoring scheme. The maximum likelihood estimates, Fisher Information matrix, and the asymptotic variance and covariance matrix are obtained. The confidence intervals of the estimators are also obtained. Furthermore, a simulation study is conducted to check the accuracy of the findings. [ABSTRACT FROM AUTHOR]

In this article, a constant-stress partially accelerated life test model of high reliability products and materials with type-II censored data from the linear failure rate distribution is considered. Two different methods of estimation likelihood and Bayesian are used to estimate the unknown parameters of the model. The maximum likelihood estimates of the model parameters are obtained using the Newton–Raphson technique. The posterior means and posterior variances are derived under the squared error loss function using Lindley's approximation procedure. The advantages of this approximation are discussed. Monte Carlo simulations are made for comparing and evaluating the performance of the proposed methods of estimation. [ABSTRACT FROM AUTHOR]

This paper considers both likelihood and Bayesian estimations of a constant-stress partially accelerated life test model with type-I censored data from the linear failure rate distribution. The maximum likelihood estimates of the model parameters are obtained using Newton–Raphson technique. The posterior means and posterior variances are obtained under the squared error loss function using Lindley's approximation procedure. The advantages of this approximation are exposed. Monte Carlo simulations are prepared under different sizes of samples and different parameter values for comparing and evaluating the proposed methods of estimation. [ABSTRACT FROM AUTHOR]

In this article, the case of failure-censored constant-stress partially accelerated life test for highly reliable materials or devices assuming the linear failure rate distribution is considered. The maximum likelihood estimates of the distribution parameters and the acceleration factor are obtained. In order to evaluate the performance, the mean squared errors are calculated using different sizes of samples. In addition, the approximate confidence intervals of model parameters are constructed. For illustrative purposes, Monte Carlo simulation studies are offered. [ABSTRACT FROM AUTHOR]

This paper discusses the parameter estimation by Bayesian method when the thermal aging lifetime follows the log-normal distribution and the sample is a general progressive type-II censoring from a constant-stress accelerated life test. The Bayes estimates cannot be obtained in an inexplicit form, and an approximate one is solved by the hybrid Markov chain Monte-Carlo method. The thermal aging life data are presented to illustrate proposed method. [ABSTRACT FROM AUTHOR]

The availability of engineering strength data on shape memory alloys (SMAs) under cyclic thermal activation (functional fatigue) is central to the rational design of smart actuators based on these materials. Test results on SMAs under functional fatigue are scarce in the technical literature and the few data available are mainly limited to constant-stress loading. Since the SMA elements used within actuators are normally biased by elastic springs or by another SMA element, their stress state is far from constant in operation. The mismatch between actual working conditions and laboratory arrangements leads to suboptimal designs and undermines the prediction of the actuator lifetime. This paper aims at bridging the gap between experiment and reality. Four test procedures are planned, covering most of the typical situations occurring in practice: constant-stress, constant-strain, constant-stress with limited maximum strain and linear stress-strain variation with limited maximum strain. The paper describes the experimental apparatus specifically designed to implement the four loading conditions and presents fatigue results obtained from commercial NiTi wires tested under all those protocols.

The rational design of smart actuators based on shape memory alloys requires reliable strength data from the thermo-mechanical cycling of the material (functional fatigue). Functional tests results do not abound in the technical literature and the few data available are mostly limited to the condition of constant applied stress, which is hardly achieved in operation. The disagreement between actual working conditions and laboratory conditions leads to suboptimal designs and undermines the prediction of the life of the actuator. To bridge the gap between experiment and reality, this paper envisions four cyclic tests spanning the range of loadings which can occur in practice: constant-stress, constant-strain, constant-stress with limited maximum strain and linear stress–strain cycle. Commercial NiTi wires (0.15 mm diameter) are tested under constant-stress, constant-strain and constant stress with limited maximum strain conditions using a custom machine and the disclosed results are critically discussed. [ABSTRACT FROM AUTHOR]

The availability of engineering strength data on shape memory alloys (SMAs) under cyclic thermal activation (functional fatigue) is central to the rational design of smart actuators based on these materials. Test results on SMAs under functional fatigue are scarce in the technical literature and the few data available are mainly limited to constant-stress loading. Since the SMA elements used within actuators are normally biased by elastic springs or by another SMA element, their stress state is far from constant in operation. The mismatch between actual working conditions and laboratory arrangements leads to suboptimal designs and undermines the prediction of the actuator lifetime. This paper aims at bridging the gap between experiment and reality. Four test procedures are planned, covering most of the typical situations occurring in practice: constant-stress, constant-strain, constant-stress with limited maximum strain and linear stress-strain variation with limited maximum strain. The paper describes the experimental apparatus specifically designed to implement the four loading conditions and presents fatigue results obtained from commercial NiTi wires tested under all those protocols. [ABSTRACT FROM AUTHOR]

The paper considers the case of constant-stress partially accelerated life testing (CSPALT) when two stress levels are involved under type-I censoring. The lifetimes of test items are assumed to follow a two-parameter Pareto lifetime distribution. Maximum-likelihood method is used to estimate the parameters of CSPALT model. Confidence intervals for the model parameters are constructed. Optimum CSPALT plans that determine the best choice of the proportion of test units allocated to each stress are developed. Such optimum test plans minimize the generalized asymptotic variance of the maximum-likelihood estimators of the model parameters. For illustration, Monte Carlo simulation studies are presented. [ABSTRACT FROM AUTHOR]