Thesis (doctoral)--Rijksuniversiteit te Groningen, 1995. / Summary in Dutch. Material type: Dissertations. Includes bibliographical references (p. 283-291).

The demand for energy and cost efficient buildings has made architects and contractors more aware of the resources consumed by the built environment. While the actual economic and environmental costs of future construction can never be completely predicted, energy simulations and cost modeling have become accepted ways to guide the design and construction process by comparing possible outcomes. These tools are now commonplace in the construction industry, and researchers are continuing to develop new and innovative strategies to optimize building design and construction. Previous research has proven that genetic algorithms are effective methods to evaluate and optimize building design in situations that contain a large number of possible solutions. The technique makes a computationally difficult multi-optimization process possible but is still a reactive and time consuming process that focuses on evaluation rather than solution generation. This research presented in this paper builds upon established multi-objective optimization techniques that use an energy simulator to estimate a conceptual building’s energy use as well as construction cost. The study compares simulations of a simplified model of a 3-story inpatient hospital located in Atlanta, Georgia using a defined set of variables. A combined global minimum of annual energy consumption and total construction is sought after using a method that utilizes a genetic algorithm. The second phase of this research uses a modified approach that combines the traditional genetic algorithm with a seeding method that utilizes previous results. A new set of simulations were established that duplicates the initial trials using a slightly modified set of design variables. The simulation was altered, and the phase one trials were utilized as the first generation of simulated solutions. The objective of this thesis is to explore one method of making energy use and cost estimating more accessible to the construction industry by combining simulation optimization and indexing. The results indicate that this study’s proposed augmented approach has potential benefits to building design optimization, although more research is required to validate this hypothesis in its entirety. This study concludes that the proposed approach can potentially reduce the time needed for individual optimization exercises by creating a cumulative, robust catalog of previous computations that will inform and seed future analyses. The research was conducted in five general stages. The first part defines the research problem and scope of research to be conducted. In the second part, the concepts of genetic algorithms and energy simulation are explored in a comprehensive literature review. The remaining parts explain the trial simulations performed in this study. Part three explains the experiment’s methodology, and part four describes the simulation results. The fifth and final part looks at what the possible conclusions that can be made from analyzing the study’s results.

The interest in creating and detecting electromagnetic waves carryingangular momentum in such a way that they form helical wavefronts,so called "twisted light'', has increased in recent decades.One possible way of generating such waves at radio frequenciesis to use a circular phased antenna array, where a larger relativephasing of the antenna elements corresponds to more twist of thewavefront per wavelength.However, analytical computations of the radiated power, and in turn theamountof emitted angular momentum, displays a quite rapid decrease with increasedphasing. This decrease in intensity may cause problems when alarge range of twisting is desired; for instance, as a means to encodeand transmit information. We have found that the decrease in radiatedpower does not haveany explicit relation to the beam being endowed with angular momentum.Instead, the decrease in emitted power can be explained byelectromagnetic couplingof the antenna elements in the array and that energy conservationholds, because an equal decrease in power is seen at the input of the array.We also show that a similar discrepancy is seen between the incomingand the total diffracted power in Young's classic double slit experiment,which, having only two slits, cannot provide any twisted light.The source of that discrepancy should be of a different origin.Although an explanation in terms of surface plasmons was recently givenin the literature, that is only applicable to metal screens. A general explanation of the problem therefore remains to be found.

Environmental, social, and economic pressure on energy issues has been a serious and urgent concern in countries like Japan, which is heavily reliant on imported energy. After the Fukushima incident in March 2011, energy issues, notably nuclear energy maters, have drawn a special attention in Japan. For long-term and promising solutions for the issue, demand side of the energy consumption at individual level should be focused. This study hence was carried out to find out possibility of sustainable energy consumption in Japan at individual level and key barriers and drivers to change behavior for energy conservation. 7 in-depth interviews were conducted to examine public reception on energy issues, and barriers and drivers to trigger energy conservation behavior among Japanese people. Also, perspective on energy issues from Japanese government and Japan Business Federation were comparably analyzed. The results identified that the Fukushima incident has little impact on people’s behavior, while there has been increasing anxiety on energy systems among them. The Fukushima incident itself therefore does not seem to affect energy conservation behavior among the Japanese. Rather, it can be assumed that energy conservation can be triggered by personal aspects or situational aspects such as perception on preferable outcome, perceived easiness of achieving the behavior, moral norm (sense of “mottainai”), past habit, and community level of social mood on energy conservation. On the other hand, family support and discomfort were found to prevent from making the behavior to occur. Moreover, since there was an evident distrust of the public towards the government, it was difficult to share the same energy issues between the two sectors, hence, restoration of the distrust is a crucial challenge for the government.

University of Macau / Faculty of Science and Technology / Department of Electromechanical Engineering

Purpose/aim This study is about environmental protection and energy conservation in the China vehicle market. Based on that, we focus on and comparison of combustion vehicles with hybrid vehicles.Design/method/approach Data was collected through questionnaire. The analysis includes a description of the sample and chi-square tests. We analyze two different particular engines (combustion engine vehicles and hybrid electric vehicles) and our single environment. We compare these two engine vehicles, and analyze the trends of the market. We use scientific data and existing theories to analyze the vehicles, including “lifecycle costs” “CO2 emissions”, “Greenhouse gas”, “Consumers perception”, “Full Costing”, “PPC (Production Possibilities Curve)”, “Supply Demand Curve”, and “Green Taxes”.Findings We conclude that hybrid engine vehicles are environmentally friendly and energy conserving, but they have higher lifecycle costs. The analysis also shows that different ages, education levels and regions affect the customers’ preferences for these two kinds of vehicles.Originality/value Our original idea is the problems of hybrid vehicles and how to support and popularize hybrid vehicles depends on the exact national conditions and policies implemented. However, consumers might not be able to accept the “environmental protection and energy conservation” concept immediately, because it’s difficult to change the consumption concept of a generation or culture. Therefore, the government should carry out policies that are suitable for their local region to update the consumption concepts of the consumers and promote the new energy vehicles. Thus, the goal of environmental protection and energy conservation can be reached.

Wireless channels are vulnerable to interception. In some applications an end-to-end secure data transfer is required. However the use of cryptographic functions in communication over a wireless channel increases sensitivity to channel errors. As a result, the connection characteristics in terms of delay, throughput, and transmission energy worsen. Transmission energy is a key issue in some secure end-to-end wireless applications especially if they are running on mobile handheld devices with a limited source of energy such as batteries. That is why in most secure end-to-end wireless connections, the connection is dropped in poor channel conditions. In this thesis, models are proposed by which the performance is improved and transmission energy is lowered. A combination of a cross-layer controller, K Best Likelihood (K-BL) channel decoder, and a keyed error detection algorithm in the novel model supports the authorized receivers by a higher throughput, lower delay mean, and less transmission energy in a certain range of the Signal to Noise Ratio (SNR). This is done at the expense of additional computation at the receiving end. Ttradeoffs are examined and the simulation results of the new model are compared with those of conventional wireless communication systems. Another model is devised to mitigate the energy consumption of the Turbo Code channel decoder. The overall decoding energy consumption for each packet can be lowered by reducing the average number of iterations in the Turbo Code channel decoder. The proposed models achieve better energy consumption by reducing the number of iterations in a channel decoder that uses the Turbo decoder and by reducing the number of retransmissions in a trellis channel decoder. Furthermore, the security enhancement of the novel models is assessed in terms of the extent to which the enhancement is fully achieved.

Signal-scale cooperation is a class of techniques designed to harness the same gains offered by multi-antenna communication in scenarios where devices are too small to contain an array of antennas. While the potential improvements in reliability at the physical layer are well known, three key challenges must be addressed to harness these gains at the medium access layer: (a) the distributed synchronization and coordination of devices to enable cooperative behavior, (b) the conservation of energy for devices cooperating to help others, and (c) the management of increased inter-device interference caused by multiple spatially separate transmissions in a cooperative network. In this thesis, we offer three contributions that respectively answer the above three challenges. First, we present two novel cooperative medium access control protocols: Distributed On-demand Cooperation (DOC) and Power-controlled Distributed On-demand Cooperation (PDOC). These protocols utilize negative acknowledgments to synchronize and trigger cooperative relay transmissions in a completely distributed manner. Furthermore, they avoid cooperative transmissions that would likely be unhelpful to the source of the traffic. Second, we present an energy conservation algorithm known as Distributed Energy-Conserving Cooperation (DECC). DECC allows devices to alter their cooperative behavior based on measured changes to their own energy efficiency. With DECC, devices become self-aware of the impact of signal-scale cooperation -- they explicitly monitor their own performance and scale the degree to which they cooperate with others accordingly. Third and finally, we present a series of protocols to combat the challenge of inter-device interference. Whereas energy efficiency can be addressed by a self-aware device monitoring its own performance, inter-device interference requires devices with network awareness that understand the impact of their behavior on the devices around them. We investigate and quantify the impact of incomplete network awareness by proposing a modeling approximation to derive relaying policy behaviors. We then map these policies to protocols for wireless channels.

Wireless channels are vulnerable to interception. In some applications an end-to-end secure data transfer is required. However the use of cryptographic functions in communication over a wireless channel increases sensitivity to channel errors. As a result, the connection characteristics in terms of delay, throughput, and transmission energy worsen. Transmission energy is a key issue in some secure end-to-end wireless applications especially if they are running on mobile handheld devices with a limited source of energy such as batteries. That is why in most secure end-to-end wireless connections, the connection is dropped in poor channel conditions. In this thesis, models are proposed by which the performance is improved and transmission energy is lowered. A combination of a cross-layer controller, K Best Likelihood (K-BL) channel decoder, and a keyed error detection algorithm in the novel model supports the authorized receivers by a higher throughput, lower delay mean, and less transmission energy in a certain range of the Signal to Noise Ratio (SNR). This is done at the expense of additional computation at the receiving end. Ttradeoffs are examined and the simulation results of the new model are compared with those of conventional wireless communication systems. Another model is devised to mitigate the energy consumption of the Turbo Code channel decoder. The overall decoding energy consumption for each packet can be lowered by reducing the average number of iterations in the Turbo Code channel decoder. The proposed models achieve better energy consumption by reducing the number of iterations in a channel decoder that uses the Turbo decoder and by reducing the number of retransmissions in a trellis channel decoder. Furthermore, the security enhancement of the novel models is assessed in terms of the extent to which the enhancement is fully achieved.

Motivated by the necessity to consider probabilistic approaches to future designs, the main objective of this thesis was to develop and characterize energy efficient probabilistic CMOS (PCMOS) circuits that can be used to implement low energy computing platforms. The simplest circuit characterized was a PCMOS inverter (switch). An analytical model relating the energy consumption per switching (E) of this switch to its probability of correctness, p was derived. This characterization can also be used to evaluate the energy and performance savings that are achieved by PCMOS switch based computing platforms. The characterization of a PCMOS inverter was also extended to larger circuits whose probabilistic behavior was analyzed by first developing probability models of primitive gates, which were then input to a graph-based model to find the probabilities of larger circuits. The analysis of larger probabilistic circuits provides a basis for analyzing probabilistic behaviors due to noise in future technologies, and can be used in probabilistic design and synthesis methods to improve circuit reliability. Another important design criterion is the speed of a PCMOS circuit. The trade-offs between the energy, speed, and p of PCMOS circuits were also analyzed. Based on this study, various methods were proposed to optimize energy delay product (EDP) and p under given constraints on p, performance, and EDP. The sensitivity of the analysis with respect to variations in temperature, supply voltage, and threshold voltage was also considered.