Experimental Investigation and Numerical Optimization of Dual Evaporator Refrigerator

Improving energy efficiency and reducing the cost of the appliance simultaneously is a continuing challenge for refrigerator manufacturers. While conventional system configuration is based on a single evaporator vapor compression cycle, there are several other system configurations that can offer benefits over it. For example, a dual evaporator (one evaporator for freshfood and one for freezer) offers several benefits such as increased efficiency, isolation of odors, and higher humidity levels in the freshfood compartment. Engineers typically use extensive experimentation to optimize the system. This approach takes significant time and resources. Although optimization studies exists for a conventional single evaporator cycle, studies for dual evaporator cycle optimization are limited. Most manufacturers do not explore complex architecture due to time consuming, labor intensive and expensive development procedures. This study presents experimental results obtained from a prototype dual evaporator refrigerator. Further, this study presents a physics-based model and a multi-objective optimization methodology that demonstrates how engineers can optimize a refrigeration system by considering multiple objectives simultaneously. The study presents example optimization results for simultaneously minimizing cost and maximizing performance within a specified design space. Optimization of the novel design uses a genetic algorithm-based optimizer in conjunction with a response surface based metamodel. Using optimization techniques, we can arrive at lowest cost design relatively quickly as shown in the analysis. More work needs to be done to validate optimized solutions as well as alternate methods to improve temperature control

Model predictive control techniques for hybrid systems

This paper describes the main issues encountered when applying model predictive control to hybrid processes. Hybrid model predictive control (HMPC) is a research field non-fully developed with many open challenges. The paper describes some of the techniques proposed by the research community to overcome the main problems encountered. Issues related to the stability and the solution of the optimization problem are also discussed. The paper ends by describing the results of a benchmark exercise in which several HMPC schemes were applied to a solar air conditioning plant.Ministerio de Eduación y Ciencia DPI2007-66718-C04-01Ministerio de Eduación y Ciencia DPI2008-0581

Modelling of heat emitters embedded within third order lumped parameter building envelope model

A dynamic modelling approach for heat emitters embedded within an existing third order lumped parameter building envelope model is reported in this work. The model has been found to provide more accurate results with negligible expense of computational time compared to a conventional quasi-dynamic model. The dynamic model also is preferred over the quasi-dynamic model as it allows for modelling emitters with high thermal capacity such as under-floor heating. Recommendation for this approach is justified through a series of analyses and comparative tests for various circuit options, timesteps and control volumes

Screening of energy efficient technologies for industrial buildings' retrofit

This chapter discusses screening of energy efficient technologies for industrial buildings' retrofit

The Kinetic Basis of Self-Organized Pattern Formation

In his seminal paper on morphogenesis (1952), Alan Turing demonstrated that different spatio-temporal patterns can arise due to instability of the homogeneous state in reaction-diffusion systems, but at least two species are necessary to produce even the simplest stationary patterns. This paper is aimed to propose a novel model of the analog (continuous state) kinetic automaton and to show that stationary and dynamic patterns can arise in one-component networks of kinetic automata. Possible applicability of kinetic networks to modeling of real-world phenomena is also discussed.Comment: 8 pages, submitted to the 14th International Conference on the Synthesis and Simulation of Living Systems (Alife 14) on 23.03.2014, accepted 09.05.201

Review of selection criteria for sensor and actuator configurations suitable for internal combustion engines

This literature review considers the problem of finding a suitable configuration of sensors and actuators for the control of an internal combustion engine. It takes a look at the methods, algorithms, processes, metrics, applications, research groups and patents relevant for this topic. Several formal metric have been proposed, but practical use remains limited. Maximal information criteria are theoretically optimal for selecting sensors, but hard to apply to a system as complex and nonlinear as an engine. Thus, we reviewed methods applied to neighboring fields including nonlinear systems and non-minimal phase systems. Furthermore, the closed loop nature of control means that information is not the only consideration, and speed, stability and robustness have to be considered. The optimal use of sensor information also requires the use of models, observers, state estimators or virtual sensors, and practical acceptance of these remains limited. Simple control metrics such as conditioning number are popular, mostly because they need fewer assumptions than closed-loop metrics, which require a full plant, disturbance and goal model. Overall, no clear consensus can be found on the choice of metrics to define optimal control configurations, with physical measures, linear algebra metrics and modern control metrics all being used. Genetic algorithms and multi-criterial optimisation were identified as the most widely used methods for optimal sensor selection, although addressing the dimensionality and complexity of formulating the problem remains a challenge. This review does present a number of different successful approaches for specific applications domains, some of which may be applicable to diesel engines and other automotive applications. For a thorough treatment, non-linear dynamics and uncertainties need to be considered together, which requires sophisticated (non-Gaussian) stochastic models to establish the value of a control architecture

Atmospheric Cloud Physics Laboratory. Requirements review

Progress in engineering of the atmospheric cloud physics laboratory is documented. Science requirements to be used for the remainder of the study are discussed