MRC Laboratory of Molecular Biology
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Dynamic exergy analysis: From industrial data to exergy flows
No full textAs the power and transport sectors decarbonize, industrial emissions will become the main focus of decarbonization efforts. Exergy analysis provides a combined material and energy efficiency approach to assess industrial plants, both of which are necessary to tackle industrial emissions. Existing studies typically use simulated, static data that cannot inform real plant operators. This paper performs an exergy analysis on data spanning 2 years from 311 sensors of a real ammonia production site. We develop methods to overcome unique data challenges associated with real industrial data processing, visualize resource flows in Sankey diagrams, and estimate exergy indicators for both the steam methane reforming plant and its constituent processes. We evaluate average conventional and transit exergy efficiencies for the plant (71%, 15%), primary reformer (86%, 40%), secondary reformer (96%, 71%), high-temperature shift (99.7%, 77%), combustor (56%, 55%), and heat exchange section (85%, 82%). Overall exergy losses are 80 MW; the primary reformer and combustor are the two processes with the highest losses at 35 and 33 MW, respectively. Such an analysis can inform both improvement projects and performance finetuning of a real plant while being applicable to any industrial site. Increased availability of cheap wireless sensors and a shift to Industry 4.0 can enable higher resolution and real-time performance monitoring
Losses in the Saturated Iron-Core Superconducting Fault Current Limiter for VSC-HVDC System
No full textThis paper presents the loss analysis on the saturated iron-core superconducting fault current limiter (SISFCL) for a VSC-HVDC transmission system. The numerical model of SISFCL as well as its loss calculation on superconducting parts were carried out by the finite-element method (FEM) using the H-formulation merged into the commercial package COMSOL. The SISFCL model was established for a practical ±10 kV VSC-HVDC system, and the fault current situation was simulated using the PSCAD with a SISFCL. The capability of fault current limiting was verified using the analysis of electromagnetic characteristics, and the corresponding patterns of magnetic field in the iron-core were studied. During the process of fault current limiting, the instantaneous power losses in the superconducting components were studied with the increasing DC bias current. Even in a DC grid system, results proved there were considerable amounts of losses occurred in the superconducting parts, when the SISFCL encountered the fault currents
Tensile Strength of Artificially Cemented Sandstone Generated via Microbially Induced Carbonate Precipitation.
No full textArtificially bio-cemented sands treated with microbially induced calcite precipitation are weakly cemented rocks representing intermediate materials between locked and carbonate sands. Variations in cementation significantly affect the strength of sample, particularly tensile stregth. The modes of fracture and the surface characteristics resulting from the indirect tensile strength tests (Brazilian tests) are strongly correlated with the specimen strength and consequently the degree of cementation. This study examines the tensile strength of bio-cemented fine and coarse sands (average particle diameter 0.18 and 1.82 mm, respectively) and investigates failure modes by recording fracture evolution at both sides of specimen and surface characteristics of the reconstructed surfaces. The dimensionless slope parameter Z2 provided the best fit with respect to tensile strength while the power spectral density was a good indicator of surface anisotropy. Finally, wavelet decomposition allowed for comparison of fracture surface characteristics of the two sands ignoring the grain size effects
A Novel Linearization Method for Optical Transmitters Based on Directly-Modulated Lasers
No full textA new practical method to correct the non-linearity of directly-modulated lasers is presented and an experimental proof-of-principle demonstration is reported. High-quality NRZ transmission at 16 Gb/s is achieved using a VCSEL specified for 10 Gb/s
Surge current capability evaluation of 6.5kV SiC MOSFETs with 3D cell layouts
No full textThis paper presents for the first time a combined experimental/numerical study of the electro-thermal surge current behaviour of 6.5kV SiC MOSFETs for various cell layouts. By means of a matched TCAD model it is demonstrated that the circular (and hence also the hexagonal) topology shows an inferior surge capability to the stripe. Conversely, the ALL allows for the dissipated losses and the peak lattice temperature attained during a 10ms pulse test to be reduced in both body and channel diode mode. In this context, it is shown that the sensitivity of the device's response to the active area can be decreased at smaller pitches
Propagative broad learning for nonparametric modeling of ambient effects on structural health indicators
No full textIn this article, a novel propagative broad learning approach is proposed for nonparametric modeling of the ambient effects on structural health indicators. Structural health indicators interpret the structural health condition of the underlying dynamical system. Long-term structural health monitoring on in-service civil engineering infrastructures has demonstrated that commonly used structural health indicators, such as modal frequencies, depend on the ambient conditions. Therefore, it is crucial to detrend the ambient effects on the structural health indicators for reliable judgment on the variation of structural integrity. However, two major challenging problems are encountered. First, it is not trivial to formulate an appropriate parametric expression for the complicated relationship between the operating conditions and the structural health indicators. Second, since continuous data stream is generated during long-term structural health monitoring, it is required to handle the growing data efficiently. The proposed propagative broad learning provides an effective tool to address these problems. In particular, it is a model-free data-driven machine learning approach for nonparametric modeling of the ambient-influenced structural health indicators. Moreover, the learning network can be updated and reconfigured incrementally to adapt newly available data as well as network architecture modifications. The proposed approach is applied to develop the ambient-influenced structural health indicator model based on the measurements of 3-year full-scale continuous monitoring on a reinforced concrete building
Maintenance service optimization in smart buildings through ultrasonic sensors network
No full textOccupancy monitoring in smart buildings has great potential to improve their operational performance. One of the most common applications concerns the dynamic adaptation of indoor conditions according to the occupancy variation. However, other implementations are possible. Occupancy data could also enhance maintenance smart contracts management, especially if coupled with a contracts’ management system as blockchain through which it is possible to achieve higher reliability and trust in transactions. In this article, a methodology to monitor occupancy data with a low-cost network, composed by a set of ultrasonic sensors, is presented. To ensure the collection of consistent data, different tests were performed for defining a convenient configuration for their installation. Following the proposed methodology, gathered data are processed and stored into a digital asset model associated with the building maintenance plan. Once a predefined threshold is reached, the system triggers a maintenance alert to the contractor to activate cleaning operations. The proposed approach enables an enhancement of the automation of maintenance management operations in a cost-effective manner. However, further validation trials are required to test the flexibility of its application in different space types
Information and Communication Theoretical Understanding and Treatment of Spinal Cord Injuries: State-of-the-art and Research Challenges
No full textAmong the various key networks in the human body, the nervous system occupies central importance. The debilitating effects of spinal cord injuries (SCI) impact a significant number of people throughout the world, and to date, there is no satisfactory method to treat them. In this paper, we review the major treatment techniques for SCI that include promising solutions based on information and communication technology (ICT) and identify the key characteristics of such systems. We then introduce two novel ICT-based treatment approaches for SCI. The first proposal is based on neural interface systems (NIS) with enhanced feedback, where the external machines are interfaced with the brain and the spinal cord such that the brain signals are directly routed to the limbs for movement. The second proposal relates to the design of self-organizing artificial neurons (ANs) that can be used to replace the injured or dead biological neurons. Apart from SCI treatment, the proposed methods may also be utilized as enabling technologies for neural interface applications by acting as bio-cyber interfaces between the nervous system and machines. Furthermore, under the framework of Internet of BioNano Things (IoBNT), experience gained from SCI treatment techniques can be transferred to nano communication research
Reconciling the Sustainable Manufacturing of Commodity Chemicals with Feasible Technoeconomic Outcomes
No full text The manufacturing industry must diverge from a ‘take, make and waste’ linear production paradigm towards more circular economies. Truly sustainable, circular economies are intrinsically tied to renewable resource flows, where vast quantities need to be available at a central point of consumption. Abundant, renewable carbon feedstocks are often structurally complex and recalcitrant, requiring costly pre-treatment to harness their potential fully. As such, the heat integration of supercritical water gasification and aerobic gas fermentation, unlocks the promise of renewable feedstocks such as lignin. This study models the technoeconomics and life cycle assessment for the sustainable production of the commodity chemicals, isopropanol and acetone, from gasified Kraft black liquor. The investment case is underpinned by rigorous process modelling informed by published continuous gas fermentation experimental data. Time series analyses support the price forecasts for the solvent products. Furthermore, a Monte Carlo simulation frames an uncertain boundary for the technoeconomic model. The technoeconomic analysis demonstrates that production of commodity chemicals priced at ~$1000 per ton is within reach of aerobic gas fermentation. In addition, owed to the sequestration of biogenic carbon into the solvent products, negative greenhouse gas emissions are achieved within a cradle-to-gate life cycle assessment framework. As such, the heat integrated aerobic gas fermentation platform has promise as a best-in-class technology for the production of a broad spectrum of renewable commodity chemicals. </jats:p
The prevalence of burnout, risk factors, and job-related stressors in gastroenterologists: A systematic review
No full textBackground and Aims: Burnout is an important occupational hazard, and the scale of the problem within gastroenterology remains poorly understood. The primary objective of this study was to understand the prevalence of burnout in gastroenterology and ascertain if there was a common prevalence within the field. The secondary objective was to identify factors and job-related stressors that commonly contribute to burnout in gastroenterologists. Methods: Systematic searches were conducted in PubMed, Scopus, Cochrane, and PsycINFO by two reviewers independently for articles published to 1 September 2020. The primary outcome measure was the reported prevalence of burnout in gastroenterologists. The secondary outcome measures were (i) the prevalence of non-somatic burnout symptoms (emotional exhaustion, depersonalization, and low personal accomplishment) and (ii) the frequency of risk factors and stressors reported in studies. Data were presented, and limited meta-analyses discussed. Results: Data were extracted from 11 studies. 54.5% (6/11) of these studies reported the prevalence of burnout in gastroenterologists; this ranged from 18.3% to 64.4%. Similar to burnout prevalence, burnout symptoms showed geographical variation and were common in gastroenterologists (up to 63.9%). Factors associated with work volume, age, and female gender were the three most frequently reported risk factors for increased levels of stress and burnout in 72.7% (8/11), 54.5% (6/11), and 45.5% (5/11) of studies, respectively. Significant methodological and clinical heterogeneity was observed. Conclusions: Burnout and its non-somatic symptoms are common in gastroenterologists, but the syndrome is understudied within the field. Further research and good quality data are needed to help address the problem