The Berkeley Comfort Model is based on the Stolwijk model of human thermal regulation but includes several signiÿcant improvements. Our new model allows an unlimited body segments (compared to six in the Stolwijk model). Each segment is modeled as four body layers (core, muscle, fat, and skin tissues) and a clothing layer. Physiological mechanisms such as vasodilation, vasoconstriction, sweating, and metabolic heat production are explicitly considered. Convection, conduction (such as to a car seat or other surface in contact with any part of the body) and radiation between the body and the environment are treated independently. The model is capable of predicting human physiological response to transient, non-uniform thermal environments. This paper describes the physiological algorithms as well as the implementation of the model.

Human thermal physiological and comfort models will soon be able to simulate both transient and spatial inhomogeneities in the thermal environment. With this increasing detail comes the need for anatomically specific convective and radiative heat transfer coefficients for the human body. The present study used an articulated thermal manikin with 16 body segments (head, chest, back, upper arms, forearms, hands, pelvis, upper legs, lower legs, feet) to generate radiative heat transfer coefficients as well as natural-and forced-mode convective coefficients. The tests were conducted across a range of wind speeds from still air to 5.0 m/s, representing atmospheric conditions typical of both indoors and outdoors. Both standing and seated postures were investigated, as were eight different wind azimuth angles. The radiative heat transfer coefficient measured for the whole-body was 4.5 W/m 2 per K for both the seated and standing cases, closely matching the generally accepted whole-body value of 4.7 W/m 2 per K. Similarly, the whole-body natural convection coefficient for the manikin fell within the mid-range of previously published values at 3.4 and 3.3 W/m 2 per K when standing and seated respectively. In the forced convective regime, heat transfer coefficients were higher for hands, feet and peripheral limbs compared to the central torso region. Wind direction had little effect on convective heat transfers from individual body segments. A general-purpose forced convection equation suitable for application to both seated and standing postures indoors was h c =10.3v 0.6 for the whole-body. Similar equations were generated for individual body segments in both seated and standing postures.

This paper discusses a spectrum of systems that cool or heat occupants personally, termed 'personal comfort systems' (PCS), in order to quantify their ability to produce comfort in ambient temperatures that are above or below the subjects' neutral temperatures.The comfort-producing effectiveness may be quantified in terms of a temperature difference, coining the index 'corrective power' (CP). CP is defined as difference between two ambient temperatures at which equal thermal sensation is achieved -one with no PCS (the reference condition), and one with PCS in use. CP represents the degree to which a PCS system may "correct" the ambient temperature toward neutrality. CP can alternatively be expressed in terms of thermal sensation and comfort survey scale units.Published studies of PCS are reviewed to extract their CP values. Cooling CP ranges from -1 to -6K, and heating CP from 2K to 10K. The physical characteristics of the particular PCS systems are not reported in detail here, but are presented as prototypes of what is possible.Deeper understanding of PCS will require new physiological and psychological information about comfort in local body segments and subsegments, and about spatial and temporal alliesthesia. These topics present many opportunities for productive future research.

A promising trend in plasmonics involves shrinking the size of plasmon-supporting structures down to a few nanometers, thus enabling control over light–matter interaction at extreme-subwavelength scales. In this limit, quantum mechanical effects, such as nonlocal screening and size quantization, strongly affect the plasmonic response, rendering it substantially different from classical predictions. For very small clusters and molecules, collective plasmonic modes are hard to distinguish from other excitations such as single-electron transitions. Using rigorous quantum mechanical computational techniques for a wide variety of physical systems, we describe how an optical resonance of a nanostructure can be classified as either plasmonic or nonplasmonic. More precisely, we define a universal metric for such classification, the generalized plasmonicity index (GPI), which can be straightforwardly implemented in any computational electronic-structure method or classical electromagnetic approach to discriminate plasmons from single-particle excitations and photonic modes. Using the GPI, we investigate the plasmonicity of optical resonances in a wide range of systems including: the emergence of plasmonic behavior in small jellium spheres as the size and the number of electrons increase; atomic-scale metallic clusters as a function of the number of atoms; and nanostructured graphene as a function of size and doping down to the molecular plasmons in polycyclic aromatic hydrocarbons. Our study provides a rigorous foundation for the further development of ultrasmall nanostructures based on molecular plasmonics.

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