Solar-Driven Sorption Chillers for Residential Space Cooling: A Review of Recent Developments and Possible Applications in Canada

2015 ◽  
Author(s):  
Daniel Bowie ◽  
Cynthia A. Cruickshank
Keyword(s):  
High Performance ◽  
Energy Use ◽  
Peak Load ◽  
Internal Heat ◽  
Electricity Grid ◽  
Residential Sector ◽  
Absorption Chillers ◽  
Space Cooling ◽  
Recent Developments ◽  
Advanced Cycles

Energy use for space cooling has increased by 156% from 1990 to 2010 in the Canadian residential sector. In many parts of the country, the increasing use of electrically driven air-conditioners has begun to shift the peak load on the electricity grid from the coldest days of winter to the hottest days of summer. Many of Canada’s major electric utilities providers rely on fossil fuels to generate the additional capacity needed to meet the peak demand, resulting in significant greenhouse gas emissions. Solar-driven sorption chillers remain one of the possible solutions for shaving the peak loads experienced by the electricity grid. This paper presents a review of the recent developments in the research of adsorption and absorption chillers, as well as a comparison of the two technologies based on the latest published experimental results found in the literature. Adsorption chillers continue to evolve in their design, including the use of new consolidated and composite adsorbents, the integration of coated adsorbers into internal heat exchangers, and newly developed advanced cycles for heat and mass recovery. While the physical design of adsorption chillers continues to be advanced, the development of absorption chillers for solar cooling applications has largely been focused on optimizing the system as a whole through improved control strategies and the implementation of newly developed high performance solar collectors. Finally, the paper aims to assess the current state of development of solar-driven sorption chillers to provide insight into their applicability in the Canadian residential sector, as well as the remaining challenges facing this technology.

scholarly journals Sensitivity analysis of peak and annual space cooling load at simplified office dynamic building model

2019 ◽  
Vol 111 ◽  
pp. 04038
Author(s):  
Vasco Zeferina ◽  
Christina Birch ◽  
Rodger Edwards ◽  
Ruth Wood
Keyword(s):  
Energy Demand ◽  
Screening Method ◽  
Peak Load ◽  
Internal Heat ◽  
Climate Change Impacts ◽  
Building Design ◽  
Energy Performance ◽  
Design Parameters ◽  
Space Cooling ◽  
Ventilation Rates

The focused investigation of building design is necessary to understand and quantify the implication of different design parameters on their energy performance. The design of future buildings is a major challenge, as current designs may be inappropriate in a future with global warming due to climate change impacts. In addition this understanding is necessary to be able to predict timing and profile of future energy demand, which is crucial for the long-term planning of energy infrastructures – particularly electricity. In this paper, the Morris Elementary Effects method is used as a screening method, to identify the key parameters of the design and operation of office buildings that affect the estimation of space cooling peak load and annual energy demand. Internal heat gains, cooling set-point and ventilation rates are identified as the parameters with larger implications for both annual and peak space cooling demand. In future climate scenarios, the magnitude of change of annual space cooling demand is significantly (around five times) larger than the change in the peak demand. Asides from the potential increase of space cooling demand in future scenarios, the sensitivity of the space cooling demand relative to the change in design parameters is potentially much larger.

Microstructure of sputter deposited Ni-Sb ohmic contacts on GaAs

1989 ◽  
Vol 47 ◽  
pp. 450-451
Author(s):  
S. Yegnasubramanian ◽  
V.C. Kannan ◽  
R. Dutto ◽  
P.J. Sakach
Keyword(s):  
High Performance ◽  
Ohmic Contacts ◽  
Surface Defects ◽  
Pure Metal ◽  
Device Fabrication ◽  
Native Oxide ◽  
Metal Thin Films ◽  
Recent Developments ◽  
Different Temperatures ◽  
Sputter Deposited

Recent developments in the fabrication of high performance GaAs devices impose crucial requirements of low resistance ohmic contacts with excellent contact properties such as, thermal stability, contact resistivity, contact depth, Schottky barrier height etc. The nature of the interface plays an important role in the stability of the contacts due to problems associated with interdiffusion and compound formation at the interface during device fabrication. Contacts of pure metal thin films on GaAs are not desirable due to the presence of the native oxide and surface defects at the interface. Nickel has been used as a contact metal on GaAs and has been found to be reactive at low temperatures. Formation Of Ni2 GaAs at 200 - 350C is reported and is found to grow epitaxially on (001) and on (111) GaAs, but is shown to be unstable at 450C. This paper reports the investigations carried out to understand the microstructure, nature of the interface and composition of sputter deposited and annealed (at different temperatures) Ni-Sb ohmic contacts on GaAs by TEM. Attempts were made to correlate the electrical properties of the films such as the sheet resistance and contact resistance, with the microstructure. The observations are corroborated by Scanning Auger Microprobe (SAM) investigations.

What Can Digitization Do For Formulated Product Innovation and Development

2020 ◽  
Author(s):  
James McDonagh ◽  
William Swope ◽  
Richard L. Anderson ◽  
Michael Johnston ◽  
David J. Bray
Keyword(s):  
High Performance ◽  
Quality Data ◽  
High Quality Data ◽  
Base Level ◽  
Hybrid Approaches ◽  
Digital Ecosystem ◽  
Recent Developments ◽  
Chemical Simulation ◽  
High Level ◽  
Physical And Chemical

Digitization offers significant opportunities for the formulated product industry to transform the way it works and develop new methods of business. R&D is one area of operation that is challenging to take advantage of these technologies due to its high level of domain specialisation and creativity but the benefits could be significant. Recent developments of base level technologies such as artificial intelligence (AI)/machine learning (ML), robotics and high performance computing (HPC), to name a few, present disruptive and transformative technologies which could offer new insights, discovery methods and enhanced chemical control when combined in a digital ecosystem of connectivity, distributive services and decentralisation. At the fundamental level, research in these technologies has shown that new physical and chemical insights can be gained, which in turn can augment experimental R&D approaches through physics-based chemical simulation, data driven models and hybrid approaches. In all of these cases, high quality data is required to build and validate models in addition to the skills and expertise to exploit such methods. In this article we give an overview of some of the digital technology demonstrators we have developed for formulated product R&D. We discuss the challenges in building and deploying these demonstrators.<br>

scholarly journals Statistical and machine learning models for optimizing energy in parallel applications

2019 ◽  
Vol 33 (6) ◽  
pp. 1079-1097 ◽  
Author(s):  
Mark Endrei ◽  
Chao Jin ◽  
Minh Ngoc Dinh ◽  
David Abramson ◽  
Heidi Poxon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
High Performance ◽  
Large Scale ◽  
Energy Use ◽  
Parallel Applications ◽  
Learning Models ◽  
Trade Off ◽  
Time Required ◽  
Machine Learning Models

Rising power costs and constraints are driving a growing focus on the energy efficiency of high performance computing systems. The unique characteristics of a particular system and workload and their effect on performance and energy efficiency are typically difficult for application users to assess and to control. Settings for optimum performance and energy efficiency can also diverge, so we need to identify trade-off options that guide a suitable balance between energy use and performance. We present statistical and machine learning models that only require a small number of runs to make accurate Pareto-optimal trade-off predictions using parameters that users can control. We study model training and validation using several parallel kernels and more complex workloads, including Algebraic Multigrid (AMG), Large-scale Atomic Molecular Massively Parallel Simulator, and Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics. We demonstrate that we can train the models using as few as 12 runs, with prediction error of less than 10%. Our AMG results identify trade-off options that provide up to 45% improvement in energy efficiency for around 10% performance loss. We reduce the sample measurement time required for AMG by 90%, from 13 h to 74 min.

scholarly journals Towards Sustainable Energy Retrofitting, a Simulation for Potential Energy Use Reduction in Residential Buildings in Palestine

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3876
Author(s):  
Sameh Monna ◽  
Adel Juaidi ◽  
Ramez Abdallah ◽  
Aiman Albatayneh ◽  
Patrick Dutournie ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Energy Savings ◽  
Residential Buildings ◽  
Residential Building ◽  
Simulation Models ◽  
Water Heating ◽  
Heating And Cooling ◽  
Space Cooling ◽  
Cooling Loads

Since buildings are one of the major contributors to global warming, efforts should be intensified to make them more energy-efficient, particularly existing buildings. This research intends to analyze the energy savings from a suggested retrofitting program using energy simulation for typical existing residential buildings. For the assessment of the energy retrofitting program using computer simulation, the most commonly utilized residential building types were selected. The energy consumption of those selected residential buildings was assessed, and a baseline for evaluating energy retrofitting was established. Three levels of retrofitting programs were implemented. These levels were ordered by cost, with the first level being the least costly and the third level is the most expensive. The simulation models were created for two different types of buildings in three different climatic zones in Palestine. The findings suggest that water heating, space heating, space cooling, and electric lighting are the highest energy consumers in ordinary houses. Level one measures resulted in a 19–24 percent decrease in energy consumption due to reduced heating and cooling loads. The use of a combination of levels one and two resulted in a decrease of energy consumption for heating, cooling, and lighting by 50–57%. The use of the three levels resulted in a decrease of 71–80% in total energy usage for heating, cooling, lighting, water heating, and air conditioning.

Molecular materials for micro-electronics

2000 ◽  
Vol 78 (3) ◽  
pp. 231-241 ◽  
Author(s):  
M D'Iorio
Keyword(s):  
High Performance ◽  
Organic Materials ◽  
Coming Of Age ◽  
Polymeric Materials ◽  
Organic Light Emitting Diodes ◽  
Light Emitting ◽  
Light Emitting Devices ◽  
Plastic Electronics ◽  
Organic Light ◽  
Recent Developments

Molecular organic materials have had an illustrious past but the ability to deposit these as homogeneous thin films has rejuvenated the field and led to organic light-emitting diodes (OLEDs) and the development of an increasing number of high-performance polymers for nonlinear and electronic applications. Whereas the use of organic materials in micro-electronics was restricted to photoresists for patterning purposes, polymeric materials are coming of age as metallic interconnects, flexible substrates, insulators, and semiconductors in all-plastic electronics. The focus of this topical review will be on organic light-emitting devices with a discussion of the most recent developments in electronic devices.PACS Nos.: 85.60Jb, 78.60Fi, 78.55Kz, 78.66Qn, 73.61Ph, 72.80Le

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