118,336 research outputs found
Experimental tests of the operating conditions of a micro gas turbine device
The aim of this work is to analyze the performance of a commercial micro gas turbine, focusing on the analysis of the fuel consumption and the outlet compressor and turbine temperature at various rpm, and to evaluate and compare the efficiency of the device. A test bench has been assembled with the available equipment in the laboratory of the department of mechanical and aerospace engineering in Roma. By using the software supplied by the manufacturer, the evaluation of the operating performance of the device at different speeds has been performed, obtaining all the values of interest
Integration of Legacy Appliances into Home Energy Management Systems
The progressive installation of renewable energy sources requires the
coordination of energy consuming devices. At consumer level, this coordination
can be done by a home energy management system (HEMS). Interoperability issues
need to be solved among smart appliances as well as between smart and
non-smart, i.e., legacy devices. We expect current standardization efforts to
soon provide technologies to design smart appliances in order to cope with the
current interoperability issues. Nevertheless, common electrical devices affect
energy consumption significantly and therefore deserve consideration within
energy management applications. This paper discusses the integration of smart
and legacy devices into a generic system architecture and, subsequently,
elaborates the requirements and components which are necessary to realize such
an architecture including an application of load detection for the
identification of running loads and their integration into existing HEM
systems. We assess the feasibility of such an approach with a case study based
on a measurement campaign on real households. We show how the information of
detected appliances can be extracted in order to create device profiles
allowing for their integration and management within a HEMS
GREEND: An Energy Consumption Dataset of Households in Italy and Austria
Home energy management systems can be used to monitor and optimize
consumption and local production from renewable energy. To assess solutions
before their deployment, researchers and designers of those systems demand for
energy consumption datasets. In this paper, we present the GREEND dataset,
containing detailed power usage information obtained through a measurement
campaign in households in Austria and Italy. We provide a description of
consumption scenarios and discuss design choices for the sensing
infrastructure. Finally, we benchmark the dataset with state-of-the-art
techniques in load disaggregation, occupancy detection and appliance usage
mining
Micro-manufacturing : research, technology outcomes and development issues
Besides continuing effort in developing MEMS-based manufacturing techniques, latest effort in Micro-manufacturing is also in Non-MEMS-based manufacturing. Research and technological development (RTD) in this field is encouraged by the increased demand on micro-components as well as promised development in the scaling down of the traditional macro-manufacturing processes for micro-length-scale manufacturing. This paper highlights some EU funded research activities in micro/nano-manufacturing, and gives examples of the latest development in micro-manufacturing methods/techniques, process chains, hybrid-processes, manufacturing equipment and supporting technologies/device, etc., which is followed by a summary of the achievements of the EU MASMICRO project. Finally, concluding remarks are given, which raise several issues concerning further development in micro-manufacturing
Design of an Elastic Actuation System for a Gait-Assistive Active Orthosis for Incomplete Spinal Cord Injured Subjects
A spinal cord injury severely reduces the quality of life of affected people. Following the injury,
limitations of the ability to move may occur due to the disruption of the motor and sensory functions
of the nervous system depending on the severity of the lesion. An active stance-control
knee-ankle-foot orthosis was developed and tested in earlier works to aid incomplete SCI subjects
by increasing their mobility and independence. This thesis aims at the incorporation of
elastic actuation into the active orthosis to utilise advantages of the compliant system regarding
efficiency and human-robot interaction as well as the reproduction of the phyisological compliance
of the human joints. Therefore, a model-based procedure is adapted to the design of
an elastic actuation system for a gait-assisitve active orthosis. A determination of the optimal
structure and parameters is undertaken via optimisation of models representing compliant actuators
with increasing level of detail. The minimisation of the energy calculated from the positive
amount of power or from the absolute power of the actuator generating one human-like gait cycle
yields an optimal series stiffness, which is similar to the physiological stiffness of the human
knee during the stance phase. Including efficiency factors for components, especially the consideration
of the electric model of an electric motor yields additional information. A human-like
gait cycle contains high torque and low velocities in the stance phase and lower torque combined
with high velocities during the swing. Hence, the efficiency of an electric motor with a gear unit
is only high in one of the phases. This yields a conceptual design of a series elastic actuator with
locking of the actuator position during the stance phase. The locked position combined with the
series compliance allows a reproduction of the characteristics of the human gait cycle during
the stance phase. Unlocking the actuator position for the swing phase enables the selection of
an optimal gear ratio to maximise the recuperable energy. To evaluate the developed concept,
a laboratory specimen based on an electric motor, a harmonic drive gearbox, a torsional series
spring and an electromagnetic brake is designed and appropriate components are selected. A
control strategy, based on impedance control, is investigated and extended with a finite state
machine to activate the locking mechanism. The control scheme and the laboratory specimen
are implemented at a test bench, modelling the foot and shank as a pendulum articulated at the
knee. An identification of parameters yields high and nonlinear friction as a problem of the system,
which reduces the energy efficiency of the system and requires appropriate compensation.
A comparison between direct and elastic actuation shows similar results for both systems at the
test bench, showing that the increased complexity due to the second degree of freedom and
the elastic behaviour of the actuator is treated properly. The final proof of concept requires the
implementation at the active orthosis to emulate uncertainties and variations occurring during
the human gait
Supporting transient stability in future highly distributed power systems
Incorporating a substantial volume of microgeneration (consumer-led rather than centrally planed) within a system that is not designed for such a paradigm could lead to conflicts in the operating strategies of the new and existing centralised generation technologies. So it becomes vital for such substantial amounts of microgeneration among other decentralised resources to be controlled in the way that the aggregated response will support the wider system. In addition, the characteristic behaviour of such populations requires to be understood under different system conditions to ascertain measures of risk and resilience. Therefore, this paper provides two main contributions: firstly, conceptual control for a system incorporating a high penetration of microgeneration and dynamic load, termed a Highly Distributed Power System (HDPS), is proposed. Secondly, a technical solution that can support enhanced transient stability in such a system is evaluated and demonstrated
Efficient Machine-type Communication using Multi-metric Context-awareness for Cars used as Mobile Sensors in Upcoming 5G Networks
Upcoming 5G-based communication networks will be confronted with huge
increases in the amount of transmitted sensor data related to massive
deployments of static and mobile Internet of Things (IoT) systems. Cars acting
as mobile sensors will become important data sources for cloud-based
applications like predictive maintenance and dynamic traffic forecast. Due to
the limitation of available communication resources, it is expected that the
grows in Machine-Type Communication (MTC) will cause severe interference with
Human-to-human (H2H) communication. Consequently, more efficient transmission
methods are highly required. In this paper, we present a probabilistic scheme
for efficient transmission of vehicular sensor data which leverages favorable
channel conditions and avoids transmissions when they are expected to be highly
resource-consuming. Multiple variants of the proposed scheme are evaluated in
comprehensive realworld experiments. Through machine learning based combination
of multiple context metrics, the proposed scheme is able to achieve up to 164%
higher average data rate values for sensor applications with soft deadline
requirements compared to regular periodic transmission.Comment: Best Student Paper Awar
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