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.

Green Media: The Future of Wireless Multimedia Networks:Guest Editorial

By 2015, with the proliferation of wireless multimedia applications and services (e.g., mobile TV, video on demand, online video repositories, immersive video interaction, peer to peer video streaming, and interactive video gaming), and any-time anywhere communication, the number of smartphones and tablets will exceed 6.5 billion as the most common web access devices. Data volumes in wireless multimedia data-intensive applications and mobile web services are projected to increase by a factor of 10 every five years, associated with a 20 percent increase in energy consumption, 80 percent of which is multimedia traffic related. In turn, multimedia energy consumption is rising at 16 percent per year, doubling every six years. It is estimated that energy costs alone account for as much as half of the annual operating expenditure. This has prompted concerted efforts by major operators to drastically reduce carbon emissions by up to 50 percent over the next 10 years. Clearly, there is an urgent need for new disruptive paradigms of green media to bridge the gap between wireless technologies and multimedia applications.

Containing the Nanometer "Pandora-Box": Cross-Layer Design Techniques for Variation Aware Low Power Systems

The demand for richer multimedia services, multifunctional portable devices and high data rates can only been visioned due to the improvement in semiconductor technology. Unfortunately, sub-90 nm process nodes uncover the nanometer Pandora-box exposing the barriers of technology scaling-parameter variations, that threaten the correct operation of circuits, and increased energy consumption, that limits the operational lifetime of today's systems. The contradictory design requirements for low-power and system robustness, is one of the most challenging design problems of today. The design efforts are further complicated due to the heterogeneous types of designs ( logic, memory, mixed-signal) that are included in today's complex systems and are characterized by different design requirements. This paper presents an overview of techniques at various levels of design abstraction that lead to low power and variation aware logic, memory and mixed-signal circuits and can potentially assist in meeting the strict power budgets and yield/quality requirements of future systems.

Automatic extruder for processing recycled polymers with ultrasound and temperature control system

Melt viscosity is one of the main factors affecting product quality in extrusion processes particularly with regard to recycled polymers. However, due to wide variability in the physical properties of recycled feedstock, it is difficult to maintain the melt viscosity during extrusion of polymer blends and obtain good quality product without generating scrap. This research investigates the application of ultrasound and temperature control in an automatic extruder controller, which has ability to maintain constant melt viscosity from variable recycled polymer feedstock during extrusion processing. An ultrasonic modulation system has been developed and fitted to the extruder prior to the die to convey ultrasonic energy from a high power ultrasonic generator to the polymer melt. Two separate control loops have been developed to run simultaneously in one controller: the first loop controls the ultrasonic energy or temperature to maintain constant die pressure, the second loop is used to control extruder screw speed to maintain constant throughput at the extruder die. Time response and energy consumption of the control methods in real-time experiments are also investigated and reported this paper.

On the Viability of Microservers for Financial Analytics

Energy consumption and total cost of ownership are daunting challenges for Datacenters, because they scale disproportionately with performance. Datacenters running financial analytics may incur extremely high operational costs in order to meet performance and latency requirements of their hosted applications. Recently, ARM-based microservers have emerged as a viable alternative to high-end servers, promising scalable performance via scale-out approaches and low energy consumption. In this paper, we investigate the viability of ARM-based microservers for option pricing, using the Monte Carlo and Binomial Tree kernels. We compare an ARM-based microserver against a state-of-the-art x86 server. We define application-related but platform-independent energy and performance metrics to compare those platforms fairly in the context of datacenters for financial analytics and give insight on the particular requirements of option pricing. Our experiments show that through scaling out energyefficient compute nodes within a 2U rack-mounted unit, an ARM-based microserver consumes as little as about 60% of the energy per option pricing compared to an x86 server, despite having significantly slower cores. We also find that the ARM microserver scales enough to meet a high fraction of market throughput demand, while consuming up to 30% less energy than an Intel server

Regional integration of biogas – developing an intersectoral research action plan for Northern Ireland

Bioenergy is a key component of the European Union long term energy strategy across all sectors, with a target contribution of up to 14% of the energy mix by 2020. It is estimated that there is the potential for 1TWh of primary energy from biogas per million persons in Europe, derived from agricultural by-products and waste. With an agricultural sector that accounts for 75% of land area and a large number of advanced engineering firms, Northern Ireland is a region with considerable potential for an integrated biogas industry. Northern Ireland is also heavily reliant on imported fossil fuels. Despite this, the industry is underdeveloped and there is a need for a collaborative approach from research, business and policy-makers across all sectors to optimise Northern Ireland’s abundant natural resources. ‘Developing Opportunities in Bio-Energy’ (i.e. Do Bioenergy) is a recently completed project that involved both academic and specialist industrial partners. The aim was to develop a biogas research action plan for 2020 to define priorities for intersectoral regional development, co-operation and knowledge transfer in the field of production and use of biogas. Consultations were held with regional stakeholders and working groups were established to compile supporting data, decide key objectives and implementation activities. Within the context of this study it was found that biogas from feedstocks including grass, agricultural slurry, household and industrial waste have the potential to contribute from 2.5% to 11% of Northern Ireland’s total energy consumption. The economics of on-farm production were assessed, along with potential markets and alternative uses for biogas in sectors such as transport, heat and electricity. Arising from this baseline data, a Do Bioenergy was developed. The plan sets out a strategic research agenda, and details priorities and targets for 2020. The challenge for Northern Ireland is how best to utilise the biogas – as electricity, heat or vehicle fuel and in what proportions. The research areas identified were: development of small scale solutions for biogas production and use; solutions for improved nutrient management; knowledge supporting and developing the integration of biogas into the rural economy; and future crops and bio-based products. The human resources and costs for the implementation were estimated as 80 person-years and £25 million respectively. It is also clear that the development of a robust bio-gas sector requires some reform of the regulatory regime, including a planning policy framework and a need to address social acceptance issues. The Action Plan was developed from a regional perspective but the results may be applicable to other regions in Europe and elsewhere. This paper presents the methodology, results and analysis, and discussion and key findings of the Do Bioenergy report for Northern Ireland.

Mobile Wearable Communications

This special issue provides the latest research and development on wireless mobile wearable communications. According to a report by Juniper Research, the market value of connected wearable devices is expected to reach $1.5 billion by 2014, and the shipment of wearable devices may reach 70 million by 2017. Good examples of wearable devices are the prominent Google Glass and Microsoft HoloLens. As wearable technology is rapidly penetrating our daily life, mobile wearable communication is becoming a new communication paradigm. Mobile wearable device communications create new challenges compared to ordinary sensor networks and short-range communication. In mobile wearable communications, devices communicate with each other in a peer-to-peer fashion or client-server fashion and also communicate with aggregation points (e.g., smartphones, tablets, and gateway nodes). Wearable devices are expected to integrate multiple radio technologies for various applications' needs with small power consumption and low transmission delays. These devices can hence collect, interpret, transmit, and exchange data among supporting components, other wearable devices, and the Internet. Such data are not limited to people's personal biomedical information but also include human-centric social and contextual data. The success of mobile wearable technology depends on communication and networking architectures that support efficient and secure end-to-end information flows. A key design consideration of future wearable devices is the ability to ubiquitously connect to smartphones or the Internet with very low energy consumption. Radio propagation and, accordingly, channel models are also different from those in other existing wireless technologies. A huge number of connected wearable devices require novel big data processing algorithms, efficient storage solutions, cloud-assisted infrastructures, and spectrum-efficient communications technologies.

Investigation of chip formation and fracture toughness in orthogonal cutting of UD-CFRP

Features of chip formation can inform the mechanism of a machining process. In this paper, a series of orthogonal cutting experiments were carried out on unidirectional carbon fiber reinforced polymer (UD-CFRP) under cutting speed of 0.5 m/min. The specially designed orthogonal cutting tools and high-speed camera were used in this paper. Two main factors are found to influence the chip morphology, namely the depth of cut (DOC) and the fiber orientation (angle 휃), and the latter of which plays a more dominant role. Based on the investigation of chip formation, a new approach is proposed for predicting fracture toughness of the newly machined surface and the total energy consumption during CFRP orthogonal cutting is introduced as a function of the surface energy of machined surface, the energy consumed to overcome friction, and the energy for chip fracture. The results show that the proportion of energy spent on tool-chip friction is the greatest, and the proportions of energy spent on creating new surface decrease with the increasing of fiber angle.

Hierarchical Demand Response for Peak Reduction using Dantzig‐Wolfe Decomposition

Demand Response (DR) algorithms manipulate the energy consumption schedules of controllable loads so as to satisfy grid objectives. Implementation of DR algorithms using a centralised agent can be problematic for scalability reasons, and there are issues related to the privacy of data and robustness to communication failures. Thus it is desirable to use a scalable decentralised algorithm for the implementation of DR. In this paper, a hierarchical DR scheme is proposed for Peak Minimisation (PM) based on Dantzig-Wolfe Decomposition (DWD). In addition, a Time Weighted Maximisation option is included in the cost function which improves the Quality of Service for devices seeking to receive their desired energy sooner rather than later. The paper also demonstrates how the DWD algorithm can be implemented more efficiently through the calculation of the upper and lower cost bounds after each DWD iteration.

Performance and Fault Tolerance of Preconditioned Iterative Solvers on Low-Power ARM Architectures

As the complexity of computing systems grows, reliability and energy are two crucial challenges asking for holistic solutions. In this paper, we investigate the interplay among concurrency, power dissipation, energy consumption and voltage-frequency scaling for a key numerical kernel for the solution of sparse linear systems. Concretely, we leverage a task-parallel implementation of the Conjugate Gradient method, equipped with an state-of-the-art pre-conditioner embedded in the ILUPACK software, and target a low-power multi core processor from ARM.In addition, we perform a theoretical analysis on the impact of a technique like Near Threshold Voltage Computing (NTVC) from the points of view of increased hardware concurrency and error rate.

The effect of melt viscosity on thermal efficiency for single screw extrusion of HDPE

In this work, a highly instrumented single screw extruder has been used to study the effect of polymer rheology on the thermal efficiency of the extrusion process. Three different molecular weight grades of high density polyethylene (HDPE) were extruded at a range of conditions. Three geometries of extruder screws were used at several set temperatures and screw rotation speeds. The extruder was equipped with real-time quantification of energy consumption; thermal dynamics of the process were examined using thermocouple grid sensors at the entrance to the die. Results showed that polymer rheology had a significant effect on process energy consumption and thermal homogeneity of the melt. Highest specific energy consumption and poorest homogeneity was observed for the highest viscosity grade of HDPE. Extruder screw geometry, set extrusion temperature and screw rotation speed were also found to have a direct effect on energy consumption and melt consistency. In particular, specific energy consumption was lower using a barrier flighted screw compared to single flighted screws at the same set conditions. These results highlight the complex nature of extrusion thermal dynamics and provide evidence that rheological properties of the polymer can significantly influence the thermal efficiency of the process.

Experimental investigation of thermal inertia properties in hemp-lime concrete walls

Hemp-lime concrete is a sustainable alternative to standard building wall materials, with low associated embodied energy. It exhibits good hygric, acoustic and thermal properties, making it an exciting, sustainable building envelope material. When cast in temporary shuttering around a timber frame, it exhibits lower thermal conductivity than concrete, and consequently achieves low U-values in a primarily mono-material wall construction. Although cast relatively thick hemp-lime walls do not generally achieve the low U-values stipulated in building regulations. However assessment of its thermal performance through evaluation of its resistance to thermal transfer alone, underestimates its true thermal quality. The thermal inertia, or reluctance of the wall to change its temperature when exposed to changing environmental temperatures, also has a significant impact on the thermal quality of the wall, the thermal comfort of the interior space and energy consumption due to space heating. With a focus on energy reduction in buildings, regulations emphasise thermal resistance to heat transfer with only less focus on thermal inertia or storage benefits due to thermal mass. This paper investigates dynamic thermal responsiveness in hemp-lime concrete walls. It reports the influence of thermal conductivity, density and specific heat through analysis of steady state and transient heat transfer, in the walls. A novel hot-box design which isolates the conductive heat flow is used, and compared with tests in standard hot-boxes. Thermal diffusivity and effusivity are evaluated, using experimentally measured conductivity, based on analytical relationships. Experimental results evident that hemp-lime exhibits high thermal inertia. They show the thermal inertia characteristics compensate for any limitations in the thermal resistance of the construction material. When viewed together the thermal resistance and mass characteristics of hemp-lime are appropriate to maintain comfortable thermal indoor conditions and low energy operation.

Combining Bio- and Chemo-Catalysis for the Conversion of Bio-Renewable Alcohols: Homogeneous Iridium Catalysed Hydrogen Transfer Initiated Dehydration of 1,3-Propanediol to Aldehydes

Combining whole cell biocatalysis and chemocatalysis in a single reaction sequence avoids unnecessary separations, and the associated waste and energy consumption. Bacterial fermentation has been employed to convert waste glycerol from biodiesel production into 1,3-propanediol. This 1,3-propanediol can be extracted selectively from the aqueous fermentation broth using ionic liquids. 1,3-propanediol in ionic liquid solution was converted to propanal by hydrogen transfer initiated dehydration (HTID) catalysed by a Cp*IrCl2(NHC) (Cp* = pentamethylcyclopentadienyl; NHC = carbene ligand) complex. The use of an ionic liquid solvent enabled the reaction to be performed under reduced pressure, facilitating the isolation of the product, and improving the reaction selectivity. The Ir(III) catalyst in ionic liquid was found to be highly recyclable.

Inexact-aware architecture design for ultra-low power bio-signal analysis

This study introduces an inexact, but ultra-low power, computing architecture devoted to the embedded analysis of bio-signals. The platform operates at extremely low voltage supply levels to minimise energy consumption. In this scenario, the reliability of static RAM (SRAM) memories cannot be guaranteed when using conventional 6-transistor implementations. While error correction codes and dedicated SRAM implementations can ensure correct operations in this near-threshold regime, they incur in significant area and energy overheads, and should therefore be employed judiciously. Herein, the authors propose a novel scheme to design inexact computing architectures that selectively protects memory regions based on their significance, i.e. their impact on the end-to-end quality of service, as dictated by the bio-signal application characteristics. The authors illustrate their scheme on an industrial benchmark application performing the power spectrum analysis of electrocardiograms. Experimental evidence showcases that a significance-based memory protection approach leads to a small degradation in the output quality with respect to an exact implementation, while resulting in substantial energy gains, both in the memory and the processing subsystem.

Runtime Support for Adaptive Power Capping on Heterogeneous SoCs

Power capping is a fundamental method for reducing the energy consumption of a wide range of modern computing environments, ranging from mobile embedded systems to datacentres. Unfortunately, maximising performance and system efficiency under static power caps remains challenging, while maximising performance under dynamic power caps has been largely unexplored. We present an adaptive power capping method that reduces the power consumption and maximizes the performance of heterogeneous SoCs for mobile and server platforms. Our technique combines power capping with coordinated DVFS, data partitioning and core allocations on a heterogeneous SoC with ARM processors and FPGA resources. We design our framework as a run-time system based on OpenMP and OpenCL to utilise the heterogeneous resources. We evaluate it through five data-parallel benchmarks on the Xilinx SoC which allows fully voltage and frequency control. Our experiments show a significant performance boost of 30% under dynamic power caps with concurrent execution on ARM and FPGA, compared to a naive separate approach.