About: Thermostat is a(n) research topic. Over the lifetime, 7405 publication(s) have been published within this topic receiving 91734 citation(s).
Stephen P. Timoshenko1•Institutions (1)
01 Sep 1925-Journal of the Optical Society of America
Abstract: The following investigation contains a general theory of bending of a bi-metal strip submitted to a uniform heating. This theory is applied in analysis of operation of a bi-metal strip thermostat. The equations are obtained for calculating the temperature of buckling, the complete travel during buckling, and the temperature of buckling in a backward direction.. By using these equations the dimensions of the thermostat for a given temperature of operation and a given complete range of temperature can be calculated. The results obtained are based on certain ideal conditions. For example, it was assumed that the differ ence in the coefficients of expansion remained constant during heating, that the friction at the supports could be neglected and that the width
15 Oct 1985-Journal of Chemical Physics
Abstract: We derive equilibrium fluctuation expressions for the linear response of many body systems thermostated by the Nose–Hoover thermostat. We show that in the thermodynamic limit this response is the same as that of the corresponding Gaussian isothermal system. Numerical comparisons for shear flow show however that the Gaussian methods provide a significantly more efficient means of calculating the shear viscosity coefficient.
Duncan S. Callaway1•Institutions (1)
01 May 2009-Energy Conversion and Management
Abstract: This paper develops new methods to model and control the aggregated power demand from a population of thermostatically controlled loads, with the goal of delivering services such as regulation and load following. Previous work on direct load control focuses primarily on peak load shaving by directly interrupting power to loads. In contrast, the emphasis of this paper is on controlling loads to produce relatively short time scale responses (hourly to sub-hourly), and the control signal is applied by manipulation of temperature set points, possibly via programmable communicating thermostats or advanced metering infrastructure. To this end, the methods developed here leverage the existence of system diversity and use physically-based load models to inform the development of a new theoretical model that accurately predicts – even when the system is not in equilibrium – changes in load resulting from changes in thermostat temperature set points. Insight into the transient dynamics that result from set point changes is developed by deriving a new exact solution to a well-known hybrid state aggregated load model. The eigenvalues of the solution, which depend only on the thermal time constant of the loads under control, are shown to have a strong effect on the accuracy of the model. The paper also shows that load heterogeneity – generally something that must be assumed away in direct load control models – actually has a positive effect on model accuracy. System identification techniques are brought to bear on the problem, and it is shown that identified models perform only marginally better than the theoretical model. The paper concludes by deriving a minimum variance control law, and demonstrates its effectiveness in simulations wherein a population of loads is made to follow the output of a wind plant with very small changes in the nominal thermostat temperature set points.
03 Nov 2010-
TL;DR: How to use cheap and simple sensing technology to automatically sense occupancy and sleep patterns in a home, and how to use these patterns to save energy by automatically turning off the home's HVAC system, called the smart thermostat.
Abstract: Heating, ventilation and cooling (HVAC) is the largest source of residential energy consumption. In this paper, we demonstrate how to use cheap and simple sensing technology to automatically sense occupancy and sleep patterns in a home, and how to use these patterns to save energy by automatically turning off the home's HVAC system. We call this approach the smart thermostat. We evaluate this approach by deploying sensors in 8 homes and comparing the expected energy usage of our algorithm against existing approaches. We demonstrate that our approach will achieve a 28% energy saving on average, at a cost of approximately $25 in sensors. In comparison, a commercially-available baseline approach that uses similar sensors saves only 6.8% energy on average, and actually increases energy consumption in 4 of the 8 households.
01 Jan 2005-Advances in Polymer Science
Abstract: Molecular dynamics simulations rely on integrating the classical (Newtonian) equations of motion for a molecular system and thus, sample a microcanonical (constant- energy) ensemble by default. However, for compatibility with experiment, it is often desirable to sample configurations from a canonical (constant-temperature) ensemble instead. A modi- fication of the basic molecular dynamics scheme with the purpose of maintaining the temper- ature constant (on average) is called a thermostat algorithm. The present article reviews the various thermostat algorithms proposed to date, their physical basis, their advantages and their shortcomings.