Energy monitoring and quality control of a single screw extruder

Polymer extrusion, in which a polymer is melted and conveyed to a mould or die, forms the basis of most polymer processing techniques. Extruders frequently run at non-optimised conditions and can account for 15–20% of overall process energy losses. In times of increasing energy efficiency such losses are a major concern for the industry. Product quality, which depends on the homogeneity and stability of the melt flow which in turn depends on melt temperature and screw speed, is also an issue of concern of processors. Gear pumps can be used to improve the stability of the production line, but the cost is usually high. Likewise it is possible to introduce energy meters but they also add to the capital cost of the machine. Advanced control incorporating soft sensing capabilities offers opportunities to this industry to improve both quality and energy efficiency. Due to strong correlations between the critical variables, such as the melt temperature and melt pressure, traditional decentralized PID (Proportional–Integral–Derivative) control is incapable of handling such processes if stricter product specifications are imposed or the material is changed from one batch to another. In this paper, new real-time energy monitoring methods have been introduced without the need to install power meters or develop data-driven models. The effects of process settings on energy efficiency and melt quality are then studied based on developed monitoring methods. Process variables include barrel heating temperature, water cooling temperature, and screw speed. Finally, a fuzzy logic controller is developed for a single screw extruder to achieve high melt quality. The resultant performance of the developed controller has shown it to be a satisfactory alternative to the expensive gear pump. Energy efficiency of the extruder can further be achieved by optimising the temperature settings. Experimental results from open-loop control and fuzzy control on a Killion 25 mm single screw extruder are presented to confirm the efficacy of the proposed approach.

New suburbia: designing in urban resilience by closing resource cycles

By utilising a research by design methodology, the paper develops a process-based and phased design to develop a new emergent form to these neighbourhoods, one in which new productive systems are embedded into the city, at a small-scales. These include a peak-load hydro-electric project in Ligoneal; a productive landscape in Glen Cairn and a city-wide energy refurbishment utilising neighbourhood waste streams.

The three projects illustrate different ways in which place-based solutions can enact urban transformation through a process of rigorous visualisation of process, and its attendant changes in content and form of the neighbourhood, These designs, based around a process-based strategy plan, allow for a roadmap for development to be created that could change the modus operandi of an area over a relatively short period of time,. The paper demonstrates that even modest investments of productive technologies at a local scale can fundamentally change the form and the economic and environmental operation of the city in the future, and create a new resilient city, one that can have resilience built-in. This resilience allows the neighbourhood to be less externally dependent on resources, economically active and more socially just.

Building information modeling based building design optimization for sustainability

Environmental problems, especially climate change, have become a serious global issue waiting for people to solve. In the construction industry, the concept of sustainable building is developing to reduce greenhouse gas emissions. In this study, a building information modeling (BIM) based building design optimization method is proposed to facilitate designers to optimize their designs and improve buildings’ sustainability. A revised particle swarm optimization (PSO) algorithm is applied to search for the trade-off between life cycle costs (LCC) and life cycle carbon emissions (LCCE) of building designs. In order tovalidate the effectiveness and efficiency of this method, a case study of an office building is conducted in Hong Kong. The result of the case study shows that this method can enlarge the searching space for optimal design solutions and shorten the processing time for optimal design results, which is really helpful for designers to deliver an economic and environmental friendly design scheme.

Waste Management and Sustainability during the Design Phase of a Construction Project: A Qualitative Review

Waste management and sustainability are two core underlying philosophies that the construction sector must acknowledge and implement; however, this can prove difficult and time consuming. To this end, the aim of this paper is to examine waste management strategies and the possible benefits, advantages and disadvantages to their introduction and use, while also to examine any inter-relationship with sustainability, particularly at the design stage. The purpose of this paper is to gather, examine and review published works and investigate factors which influence economic decisions at the design phase of a construction project. In addressing this aim, a three tiered sequential research approach is adopted; in-depth literature review, interviews/focus groups and qualitative analysis. The resulting data is analyzed, discussed, with potential conclusions identified; paying particular attention to implications for practice within architectural firms. This research is of importance, particularly to the architectural sector, as it can add to the industry’s understanding of the design process, while also considering the application and integration of waste management into the design procedure. Results indicate that the researched topic had many advantages but also had inherent disadvantages. It was found that the potential advantages outweighed disadvantages, but uptake within industry was still slow and that better promotion and their benefits to; sustainability, the environment, society and the industry were required.

Design of an automated solar concentrator for the pyrolysis of scrap rubber

An automated solar reactor system was designed and built to carry out catalytic pyrolysis of scrap rubber tires at 550°C. To maximize solar energy concentration, a two degrees-of-freedom automated sun tracking system was developed and implemented. Both the azimuth and zenith angles were controlled via feedback from six photo-resistors positioned on a Fresnel lens. The pyrolysis of rubber tires was tested with the presence of two types of acidic catalysts, H-beta and H-USY. Additionally, a photoactive TiO<inf>2</inf> catalyst was used and the products were compared in terms of gas yields and composition. The catalysts were characterized by BET analysis and the pyrolysis gases and liquids were analyzed using GC-MS. The oil and gas yields were relatively high with the highest gas yield reaching 32.8% with H-beta catalyst while TiO<inf>2</inf> gave the same results as thermal pyrolysis without any catalyst. In the presence of zeolites, the dominant gasoline-like components in the gas were propene and cyclobutene. The TiO<inf>2</inf> and non-catalytic experiments produced a gas containing gasoline-like products of mainly isoprene (76.4% and 88.4% respectively). As for the liquids they were composed of numerous components spread over a wide distribution of C<inf>10</inf> to C<inf>29</inf> hydrocarbons of naphthalene and cyclohexane/ene derivatives.

Low-cost Process monitoring for polymer extrusion

Polymer extrusion is regarded as an energy-intensive production process, and the real-time monitoring of both energy consumption and melt quality has become necessary to meet new carbon regulations and survive in the highly competitive plastics market. The use of a power meter is a simple and easy way to monitor energy, but the cost can sometimes be high. On the other hand, viscosity is regarded as one of the key indicators of melt quality in the polymer extrusion process. Unfortunately, viscosity cannot be measured directly using current sensory technology. The employment of on-line, in-line or off-line rheometers is sometimes useful, but these instruments either involve signal delay or cause flow restrictions to the extrusion process, which is obviously not suitable for real-time monitoring and control in practice. In this paper, simple and accurate real-time energy monitoring methods are developed. This is achieved by looking inside the controller, and using control variables to calculate the power consumption. For viscosity monitoring, a ‘soft-sensor’ approach based on an RBF neural network model is developed. The model is obtained through a two-stage selection and differential evolution, enabling compact and accurate solutions for viscosity monitoring. The proposed monitoring methods were tested and validated on a Killion KTS-100 extruder, and the experimental results show high accuracy compared with traditional monitoring approaches.

ALEA: Fine-Grain Energy Profiling with Basic Block Sampling

Energy efficiency is an essential requirement for all contemporary computing systems. We thus need tools to measure the energy consumption of computing systems and to understand how workloads affect it. Significant recent research effort has targeted direct power measurements on production computing systems using on-board sensors or external instruments. These direct methods have in turn guided studies of software techniques to reduce energy consumption via workload allocation and scaling. Unfortunately, direct energy measurements are hampered by the low power sampling frequency of power sensors. The coarse granularity of power sensing limits our understanding of how power is allocated in systems and our ability to optimize energy efficiency via workload allocation.
We present ALEA, a tool to measure power and energy consumption at the granularity of basic blocks, using a probabilistic approach. ALEA provides fine-grained energy profiling via sta- tistical sampling, which overcomes the limitations of power sens- ing instruments. Compared to state-of-the-art energy measurement tools, ALEA provides finer granularity without sacrificing accuracy. ALEA achieves low overhead energy measurements with mean error rates between 1.4% and 3.5% in 14 sequential and paral- lel benchmarks tested on both Intel and ARM platforms. The sampling method caps execution time overhead at approximately 1%. ALEA is thus suitable for online energy monitoring and optimization. Finally, ALEA is a user-space tool with a portable, machine-independent sampling method. We demonstrate two use cases of ALEA, where we reduce the energy consumption of a k-means computational kernel by 37% and an ocean modelling code by 33%, compared to high-performance execution baselines, by varying the power optimization strategy between basic blocks.

An investigation of IAQ, thermal comfort and Sick Building Syndrome symptoms in UK energy efficient homes

Purpose
– Concern of the deterioration of indoor environmental quality as a result of energy efficient building design strategies is growing. Apprehensions of the effect of airtight, super insulated envelopes, the reduction of infiltration, and the reliance on mechanical systems to provide adequate ventilation (air supply) is promoting emerging new research in this field. The purpose of this paper is to present the results of an indoor air quality (IAQ) and thermal comfort investigation in UK energy efficient homes, through a case study investigation.

Design/methodology/approach
– The case study dwellings consisted of a row of six new-build homes which utilize mechanical ventilation with heat recovery (MVHR) systems, are built to an average airtightness of 2m3/m2/hr at 50 Pascal’s, and constructed without a central heating system. Physical IAQ measurements and occupant interviews were conducted during the summer and winter months over a 24-hour period, to gain information on occupant activities, perception of the interior environment, building-related health and building use.

Findings
– The results suggest inadequate IAQ and perceived thermal comfort, insufficient use of purge ventilation, presence of fungal growth, significant variances in heating patterns, occurrence of sick building syndrome symptoms and issues with the MVHR system.

Practical implications
– The findings will provide relevant data on the applicability of airtight, mechanically ventilated homes in a UK climate, with particular reference to IAQ.

Originality/value
– IAQ data of this nature is essentially lacking, particularly in the UK context. The findings will aid the development of effective sustainable design strategies that are appropriate to localized climatic conditions and sensitive to the health of building occupants.

Music for Sleeping & Waking Minds

Music for Sleeping & Waking Minds is a 8-hour composition intended for overnight listening. It features 4 performers who wear custom-designed EEG sensors. The performers rest and fall asleep as they naturally would. Over the course of one night, their brainwave activity generates a spatial audio environment. Audiences are invited to sleep or listen as they wish. Composition & concept by Gascia Ouzounian. Physiological interface and interaction design by R. Benjamin Knapp. Audio interface and interaction design by Eric Lyon.