Jan F. Kreider

Handbook of heating, ventilation, and air conditioning

INTRODUCTION TO THE BUILDINGS SECTOR FUNDAMENTALS Thermodynamic and Heat Transfer Basics Psychrometrics and Comfort ECONOMIC ASPECTS OF BUILDINGS Central and Distributed Utilities Economics & Costing of HVAC Systems HVAC EQUIPMENT AND SYSTEMS Heating Systems Air conditioning Systems Ventilation and Air Handling Systems Electrical Systems CONTROLS Controls Fundamentals Intelligent Buildings HVAC DESIGN CALCULATIONS Energy Calculations - Building Loads Simulation and Modeling - Building Energy Consumption Energy Conservation in Buildings Solar Energy System Analysis and Design OPERATION AND MAINTENANCE HVAC System Commissioning Building System Diagnostics and Preventive Maintenance APPENDICES Appendix A: Properties of Gases and Vapors Appendix B: Properties of Liquids Appendix C: Properties of Solids Appendix D: Gases and Vapors Appendix E: Composition and Heating Values of Common Fuels INDEX

ANALYTICAL MODEL FOR HEAT TRANSFER IN AN UNDERGROUND AIR TUNNEL

A simplified analytical model is developed to determine the energy performance of an underground air tunnel. The model assumes that the air tunnel-ground system reaches periodic and quasi-steady state behavior after some days of operation. The model can predict the air temperature variation along the air tunnel for any hour of the day. It can also determine the daily mean and amplitude of the total cooling/heating effect of the tunnel. Parametric analysis is conducted to determine the effect of tunnel hydraulic diameter and air flow rate on the heat transfer between ground and air inside the tunnel. The model is validated against measured data.

Analytical Model to Predict Annual Soil Surface Temperature Variation

An analytical model is developed to predict the annual variation of soil surface temperature from readily available weather data and soil thermal properties. The time variation is approximated by a first harmonic function characterized by an average, an amplitude, and a phase lag. A parametric analysis is presented to determine the effect of various factors such as evaporation, soil absorptivity, and soil convective properties on soil surface temperature. A comparison of the model predictions with experimental data is presented. The comparative analysis indicates that the simplified model predicts soil surface temperatures within ten percent of measured data for five locations.

ITPE Technique Applications to Time-Varying Three-Dimensional Ground-Coupling Problems

Approximate analytical solutions for the three-dimensional heat transfer between slab-on-grade floors and rectangular basements under steady-periodic conditions are developed using the Interzone Temperature Profile Estimation (ITPE) method. The slab-on-grade solution is the first analytical slab-on-grade solution is the first analytical solution of the time-dependent three-dimensional problem for basements. Solutions are given for the temperature field and expressions are derived for the annual heat loss. Parametric analysis is used to emphasize the effect of geometric dimensions on the magnitude and phase of h eat loss relative to ambient temperature. The results obtained are compared with those from the two-dimensional model, and the three-dimensional characteristics of heat flow from slabs and basements are examined.

Estimation of Energy Savings for Building Retrofits Using Neural Networks

This paper overviews some applications of neural networks (NNs) to estimate energy and demand savings from retrofits of commercial buildings. First, a brief background information on NNs is provided. Then, three specific case studies are described to illustrate how and when NNs can be used successfully to determine energy savings due to the implementation of various energy conservation measures in existing commercial buildings.

Tracking and stationary flat plate solar collectors : yearly collectible energy correlations for photovoltaic applications

Abstract For tracking and stationary flat plate (nonconcentrating) solar collectors, we develop easy-to-use, closed form, analytic formulae for yearly collectible energy as a function of radiation threshold. Primary applications include central-station photovoltaic systems. These correlations include the explicit dependence on: yearly average clearness index, latitude, and ground cover ratio (shading effects), and are in excellent agreement with data-based results for 26 U.S. SOLMET stations. They also incorporate appropriate functional forms that ensure accurate results for photovoltaic system design and, in particular, for systems with buy-back thresholds. Both beam and diffuse shading are treated properly and diffuse shading is found to represent a 2%–6% loss that has systematically been ignored in past studies. Sample sensitivity studies illustrate evaluation of the energetic advantage of tracking vs. stationary deployment and its significant dependence on ground cover ratio. The impact of isotropic versus anisotropic modeling of diffuse radiation is quantified and shown to give rise to non-negligible differences (up to 10%) in yearly collectible energy. We also determine an optimal tracking strategy for two-axis trackers which, however, is found to yield a 0%–2% energetic advantage relative to conventional normal-incidence tracking.

Comprehensive Evaluation of Impacts From Potential, Future Automotive Fuel Replacements

In modern society, everything from transportation to commerce to food supply is heavily dependent on the availability of cheap and plentiful energy supplies. In the past few years many have realized that the traditional sources of energy — oil and gas — are in limited supply and that we need to prepare for the approaching production maxima. It is in the interest of national economic security to investigate alternative sources of transportation energy before the extraction of existing supplies becomes prohibitively expensive. This meta-study investigates a number of potential fuels and their sources, including: • agricultural solutions - ethanol (corn and cellulosic), • agricultural solutions - biodiesel, • unconventional refining techniques such as coal-to-liquid, • oil shale retorting and tar sand processing, • traditional petroleum sources. The concentration in the current study is on transportation needs, although it is recognized that building space conditioning and electricity consumption are also significant demands for energy. The results are reported for land use, water use, input-to-output energy ratio, and carbon emissions for each fuel cycle and source. Data are given for the cases of 10, 25, and 50 percent displacements of the 2012 predicted transportation energy needs (i.e., the equivalent of 430 million gallons of gasoline per day). Cradle to grave findings indicate that some novel fuels cannot substitute for conventional fuels without consuming more water or land and emitting more greenhouse gases than fuels in use today. The most sustainable direction for the US transportation fuels sector is suggested.Copyright

Expert systems, neural networks and artificial intelligence applications in commercial building HVAC operations

Abstract For several years researchers at the JCEM have sought ways to apply various artificial intelligence methods to commercial building HVAC operations. This paper, based on two earlier articles, reports on some of the key results of work at Colorado. Expert system enhanced with neural networks trained by historical building data appear to be particularly promising for efficient and semi-automatic supervision of HVAC systems for commercial buildings. It appears that the over reliance on logic associated with expert systems alone can be reduced with a bettwe results neurl networks.

Preliminary design and economic analysis of solar-energy systems for heating and cooling of buildings

This article presents an overview of the current state of solar system design and optimization analysis for low temperature applications. It emphasizes the design of collector systems for heating and cooling of buildings and presents a simple economic analysis to determine the actual cost of thermal energy delivered by a solar collector system under given environmental conditions.

Analytical Model to Predict Nonhomogeneous Soil Temperature Variation

This paper presents an analytical model to predict the temperature variation within a multilayered soil. The soil surface temperature is assumed to have a sinusoidal time variation for both daily and annual time scales. The soil thermal properties in each layer are assumed to be uniform. The model is applied to two-layered, three-layered, and to nonhomogeneous soils. In case of two-layered soil, a detailed analysis of the thermal behavior of each layer is presented. It was found that as long as the order of magnitude of the thermal diffusivity of soil surface does not exceed three times that of deep soil ; the soil temperature variation with depth can be predicted accurately by a simplified model that assumes that the soil has constant thermal properties.