MP 2009-09

As the price of traditional fossil fuels escalates, there is increasing interest in using renewable resources, such as biomass, to meet our energy needs. Biomass resources are of particular interest to communities in interior Alaska, where they are abundant (Fresco, 2006). Biomass has the potential to partially replace heating oil, in addition to being a possible source for electric power generation (Crimp and Adamian, 2000; Nicholls and Crimp, 2002; Fresco, 2006). The communities of Tanana and Dot Lake have already installed small Garn boilers to provide space heating for homes and businesses (Alaska Energy Authority, 2009). A village-sized combined heat and power (CHP) demonstration project has been proposed in North Pole. In addition, several Fairbanks area organizations are interested in using biomass as a fuel source. For example, the Fairbanks North Star Borough is interested in using biomass to supplement coal in a proposed coal-to-liquids project, the Cold Climate Housing Research Center is planning to test a small biomass fired CHP unit, and the University of Alaska is planning an upgrade to its existing coal-fired power plant that could permit co-firing with biomass fuels. The challenge for all of these projects is in ensuring that biomass can be harvested on both an economically and ecologically sustainable basis

Can ground source heat pumps perform well in Alaska?

The long heating season and cold soils of Alaska provide a harsh testing ground for ground source heat pumps (GSHPs), even those designed and marketed for colder climates. Fairbanks, Alaska has 7,509°C heating degree-days18 (13,517°F HDD65) and only 40°C cooling degree-days18 (72°F CDD65). This large and unbalanced heating load creates a questionable environment for GSHPs. In addition, soil temperatures average around freezing (0°C/32°F); the soil may be permafrost year-round, just above freezing, or in an annual freeze-thaw cycle. In 2013 the Cold Climate Housing Research Center (CCHRC) installed a GSHP at its facility in Fairbanks. The heat pump replaced an oil-fired condensing boiler heating a 464 m2 (5,000 ft2)office space. The ground heat exchanger was installed in a marginal area underlain with permafrost near 0°C (32°F). The intent of the installation was to observe and monitor the system over a 10-year period in order to develop a better understanding of the performance of GSHPs in ground with permafrost and to help inform future design. The system enjoyed one season of better-than-expected performance, averaging a COP of 3.7its first winter. By the third winter, the COP had dropped to an annual average of 3.2 and ice had started to develop in the area around the heat extraction coils. A combination of physical monitoring and numerical modeling is used to evaluate the heat pump system

Building dynamic thermal model calibration using the Energy House facility at Salford

Thermal modelling tools have widely been used in the construction industry at the design stage, either for new build or retrofitting existing buildings, providing data for informed decision-making. The accuracy of thermal models has been subject of much research in recent decades due to the potential large difference between predicted and ‘in-use’ performance – the so called ‘performance gap’. A number of studies suggested that better representation of building physics and operation details in thermal models can improve the accuracy of predictions. However, full-scale model calibration has always been challenging as it is difficult to measure all the necessary boundary conditions in an open environment. Thus, the Energy House facility at the University of Salford – a full-sized end terrace house constructed within an environmental chamber – presents a unique opportunity to conduct full-scale model calibration. The aim of this research is to calibrate Energy House thermal models using various full-scale measurements. The measurements used in this research include the co-heating tests for a whole house retrofit case study, and thermal resistance from window coverings and heating controls with thermostatic radiator valves (TRVs). Thermal models were created using an IESVE (Integrated Environment Solutions Virtual Environment). IESVE is a well-established dynamic thermal simulation tool widely used in analysing the dynamic response of a building based on the hourly input of weather data. The evidence from this study suggests that thermal models using measured U-values and infiltration rates do perform better than the models using calculated thermal properties and assumed infiltration rates. The research suggests that better representations of building physics help thermal models reduce the performance gap. However, discrepancies still exist due to various other underlying uncertainties which need to be considered individually with each case. In relative terms, i.e., variations in percentage, the predictions from thermal models tend to be more reliable than predicting the absolute numbers

The thermal performance of window coverings in a whole house test facility with single-glazed sash windows

The residential sector is responsible for 29% of the total energy consumption of the UK, with 62% of this energy being used for space heating. Heat loss through the fabric of building elements is a crucial factor in the energy efficiency of homes, and a wide number of studies have looked at physical interventions to improve the energy efficiency of existing buildings, commonly called retrofit. This research considers the impact of window coverings on reducing heat loss from homes, a measure that is not commonly considered an energy efficiency intervention. Although the amount of glazing varies widely between homes, all windows are a significant factor contributing to heat loss. While physical changes such as double and triple glazing can improve the energy performance of buildings, the impact of curtains and blinds is not well characterised. Previous research into window coverings has been undertaken using laboratory tests, such as hotbox and small climatic chamber environments. This study presents the impact of window coverings on heat loss within a unique whole house test facility. This allows for a better replication of a real heating system and the effects that it has on localised heat transfer. This gives a more detailed picture of in situ performance, similar to that which may be found in the field

Walking cadence (steps/min) and intensity in 21-40 year olds: CADENCE-adults

Background: Previous studies have reported that walking cadence (steps/min) is associated with absolutely-defined intensity (metabolic equivalents; METs), such that cadence-based thresholds could serve as reasonable proxy values for ambulatory intensities.Purpose: To establish definitive heuristic (i.e., evidence-based, practical, rounded) thresholds linking cadence with absolutely-defined moderate (3 METs) and vigorous (6 METs) intensity.Methods: In this laboratory-based cross-sectional study, 76 healthy adults (10 men and 10 women representing each 5-year age-group category between 21 and 40 years, BMI = 24.8 +/- 3.4 kg/m 2 ) performed a series of 5-min treadmill bouts separated by 2-min rests. Bouts began at 0.5 mph and increased in 0.5 mph increments until participants: 1) chose to run, 2) achieved 75% of their predicted maximum heart rate, or 3) reported a Borg rating of perceived exertion > 13. Cadence was hand-tallied, and intensity (METs) was measured using a portable indirect calorimeter. Optimal cadence thresholds for moderate and vigorous ambulatory intensities were identified using a segmented regression model with random coefficients, as well as Receiver Operating Characteristic (ROC) models. Positive predictive values (PPV) of candidate heuristic thresholds were assessed to determine final heuristic values.Results: Optimal cadence thresholds for 3 METs and 6 METs were 102 and 129 steps/min, respectively, using the regression model, and 96 and 120 steps/min, respectively, using ROC models. Heuristic values were set at 100 steps/min (PPV of 91.4%), and 130 steps/min (PPV of 70.7%), respectively.Conclusions: Cadence thresholds of 100 and 130 steps/min can serve as reasonable heuristic thresholds representative of absolutely-defined moderate and vigorous ambulatory intensity, respectively, in 21-40 year olds. These values represent useful proxy values for recommending and modulating the intensity of ambulatory behavior and/or as measurement thresholds for processing accelerometer data.Peer reviewedCommunity Health Sciences, Counseling and Counseling Psycholog

Testing and analysis of a ground source heat pump in Interior Alaska

Thesis (M.S.) University of Alaska Fairbanks, 2019Ground source heat pumps (GSHPs) can be an efficient heating and cooling system in much of the world. However, their ability to work in extreme cold climates is not well studied. In a heating-dominated cold climate, the heat extracted from the soil is not actively replaced in the summer because there is very little space cooling. A ground source heat pump was installed at the Cold Climate Housing Research Center (CCHRC) in Fairbanks, Alaska with the intent to collect data on its performance and effects on the soil for at least ten years. Analysis shows GSHPs are viable in the Fairbanks climate; however, their performance may degrade over time. According to two previous finite element models, the CCHRC heat pump seems to reach equilibrium in the soil at a COP of about 2.5 in five to seven years. Data from the first four heating seasons of the ground source heat pump at CCHRC is evaluated. The efficiency of the heat pump degraded from an average coefficient of performance (COP) of 3.7 to a mediocre 2.8 over the first four heating seasons. Nanofluids are potential heat transfer fluids that could be used to enhance the heat transfer in the ground heat exchanger. Improved heat transfer could lower installation costs by making the ground heat exchanger smaller. A theoretical analysis of adding nanoparticles to the fluid in the ground heat exchanger is conducted. Two nanofluids are evaluated to verify improved heat transfer and potential performance of the heat pump system. Data from the CCHRC heat pump system has also been used to analyze a 2-dimensional finite element model of the system's interaction with the soil. A model based on the first four years of data is developed using Temp/W software evaluates the ground heat exchanger for a thirty-year period. This model finds that the ground heat exchanger does not lower the ground temperature in the long term.Alaska Energy Authority and the Denali Commission Emerging Energy Technology Fund grant, Alaska Housing Finance CorporationChapter 1: Thesis introduction -- 1.1 Introduction -- 1.2 Cold climate ground source heat pumps - Literature review -- 1.3 Nanofluids - Literature review -- 1.4 Objectives of this thesis and summary of chapters -- 1.5 Nomenclature -- 1.6 Greek symbols -- 1.7 Subscripts -- 1.8 References. Chapter 2: The CCHRC heat pump demonstration project -- 2.1 Introduction -- 2.2 Background -- 2.2.1 Design and installation -- 2.2.2 The heat pump unit -- 2.2.3 Maintenance and history -- 2.3 Data collection -- 2.3 Data collection -- 2.3.2 Mechanical system -- 2.4 Installation costs -- 2.4.1 Operating cost -- 2.5 Savings of the heat pump over using oil -- 2.6 CCHRC GSHP results -- 2.6.1 Observed GHE temperatures -- 2.6.2 Permafrost -- 2.6.3 Surface treatments -- 2.6.4 Heat delivered -- 2.6.5 COP -- 2.7 Discussion -- 2.8 Conclusions and recommendations -- 2.9 Nomenclature -- 2.10 References. Chapter 3: Analytical study of a cold climate ground source heat pump with Al₂O₃ nanofluid in the ground heat exchanger -- 3.1 Introduction -- 3.2 GSHP fluid properties -- 3.3 Nanofluid properties -- 3.5 Heat transfer and pumping power calculations -- 3.6 Analytical results -- 3.7 Discussion -- 3.8 Conclusions -- 3.9 Nomenclature -- 3.10 Greek symbols -- 3.11 Subscripts -- 3.12 References. Chapter 4: GSHP soil model -- 4.1 Introduction -- 4.1.1 Past soil models for this heat pump -- 4.2 Software package -- 4.2.1 Governing equations -- 4.3 Domain and grid layout -- 4.4 Material properties -- 4.5 Boundary conditions -- 4.6 Model correlation -- 4.7 Results -- 4.9 Conclusion -- 4.10 Nomenclature -- 4.11 Greek symbols -- 4.12 Subscripts -- 4.13 References. Chapter 5: Thesis conclusions and recommendations -- 5.1 Conclusions -- 5.2 Recommendations for future research -- 5.2.1 Cold climate heat pump -- 5.2.2 Nanofluids in the heat pump -- 5.2.3 Finite element model of the ground heat exchanger -- 5.3 Nomenclature -- 5.4 References

Impact of Intake and Exhaust Ducts on the Recovery Efficiency of Heat Recovery Ventilation Systems

The heat recovery efficiency of ventilation systems utilizing heat recovery ventilators (HRVs) depends not only on the heat recovery efficiency of the HRV units themselves but also on the intake and exhaust ducts that connect the HRV units to the outside environment. However, these ducts are often neglected in heat loss calculations, as their impact on the overall heat recovery efficiency of HRV systems is often not understood and, to the knowledge of the authors, a mathematical model for the overall heat recovery efficiency of HRV systems that accounts for these ducts has not been published. In this research, a mathematical model for the overall heat recovery efficiency of HRV systems that accounts for the intake and exhaust ducts was derived and validated using real-life data. The model-predicted decrease in heat recovery efficiency due to the ducts was in reasonable agreement (relative error within 20%) with the real-life measurements. The results suggest that utilizing this model allows for more correct ventilation heat loss calculations compared to using the heat recovery efficiency of the HRV unit alone, but more field studies are needed to verify the accuracy of this model in a wide range of applications

Impact of Intake and Exhaust Ducts on the Recovery Efficiency of Heat Recovery Ventilation Systems

The heat recovery efficiency of ventilation systems utilizing heat recovery ventilators (HRVs) depends not only on the heat recovery efficiency of the HRV units themselves but also on the intake and exhaust ducts that connect the HRV units to the outside environment. However, these ducts are often neglected in heat loss calculations, as their impact on the overall heat recovery efficiency of HRV systems is often not understood and, to the knowledge of the authors, a mathematical model for the overall heat recovery efficiency of HRV systems that accounts for these ducts has not been published. In this research, a mathematical model for the overall heat recovery efficiency of HRV systems that accounts for the intake and exhaust ducts was derived and validated using real-life data. The model-predicted decrease in heat recovery efficiency due to the ducts was in reasonable agreement (relative error within 20%) with the real-life measurements. The results suggest that utilizing this model allows for more correct ventilation heat loss calculations compared to using the heat recovery efficiency of the HRV unit alone, but more field studies are needed to verify the accuracy of this model in a wide range of applications