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Energy-economic analysis and optimization of a shell and tube heat exchanger using a multi-objective heat transfer search algorithm
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No data was used for the research described in the article.Acknowledgement: The work was done as part of the collaboration between Pandit Deendayal Energy University and the Heat Pipe and Thermal Management Research Group at Brunel University London, UK.This study presents the energy-economic analysis and optimization of a shell and tube heat exchanger. A water-water, segmental baffled shell and tube heat exchanger was designed using the Kern method and analysed by performing energy and economic modelling. The analysis is carried out considering the design variables on the shell side i.e. baffle cut, baffle spacing, shell diameter and tube side variables i.e. tube layout, tube outside diameter, number of tube passes and number of tubes. The multi-objective heat transfer search algorithm was used to optimize the heat exchanger for minimum total cost and maximum heat exchanger efficiency. Multiple optimal solutions were presented using the Pareto optimal curve. TOPSIS selection criteria was used to identify the optimum operating condition. Within the given bounds of the variables, the shell and tube heat exchanger can be operated at a minimum cost of 72,000 /year. The scattered distribution of shell diameter, baffle spacing, number of tube passes and number of tubes between the lower and upper bound represent their substantial role in optimizing the heat exchanger performance. The number of tubes and tube passes showed the maximum variation in efficiency, while significantly less impact was observed when the tube layout was altered
Applications of the MC-DC casting technology to 6xxx series automotive aluminium alloys
No full textThis thesis was submitted for the award of Master of Philosophy and was awarded by Brunel University LondonEnvironmental problems, such as global warming due to the ozone layer
depletion related to greenhouse gas (GHG) emissions from fossil fuels have
been drawing attention in recent years, and attempts are being made in various
fields. Efforts in the field of automobiles are being made to decrease CO2
emissions by improving fuel efficiency through producing vehicle bodies with
reduced weight, as well as electric cars, fuel-cell vehicles, etc. The characteristic
properties of aluminium, high strength to weight ratio, good formability, good
resistance to corrosion and recycling potential make it the perfect candidate to
substitute heavier materials (steel) in the car to meet the need for weight reduction
in the automotive industry. The 6xxx series alloy has been the most commonly
used for extrusion products due to its light weight, good extrudability, strong
corrosion resistance, high strength with good machining performance and
weldability.
Semi-continuous direct-chill (DC) casting is a well-established method and the
most commonly used in wrought alloy extrusion billet manufacturing. For
aluminium billets produced by direct-chill (DC) casting a fine and uniform
microstructure is always desirable. A novel direct chill (DC) casting process, melt
conditioned direct chill (MC-DC) casting process, has been developed for
production of high- quality aluminium alloy billets. In the MC-DC casting process,
a high shear device is submerged in the sump of the DC mould to provide
intensive melt shearing, which in turn, disperses potential nucleating particles,
creates a macroscopic melt flow to uniformly distribute the dispersed particles,
and maintains a uniform temperature and chemical composition throughout the
melt in the sump. Experimental results have shown that the MC-DC casting
process can produce aluminium alloy billets with a microstructure that is
comparably refined to those produced by other casting methods, while also
demonstrating a reduction in cast defects.
This work focuses on extending current knowledge of MC-DC casting process
and address the capabilities and the effect of intensive melt shearing in DC cast
billets on thermomechanical processing of 6xxx series wrought aluminium alloys,
and mechanical properties to serve the ever-increasing demands in the
automotive industry with regards to light-weighting and reducing carbon footprints in general.
The study found that the Melt Conditioned Direct Chill (MC-DC) casting process
demonstrated an ability to achieve grain sizes comparable to traditional DC
casting methods, indicating its potential for controlling microstructural
characteristics. Additionally, MC-DC casting showed some improvement in the
distribution and morphology of Fe-bearing intermetallics, contributing to a more
uniform microstructure than what is typically observed in conventional DC-GR
casting. The mechanical properties of MC-DC cast alloys, particularly in the 6xxx
series, suggested possible enhancements in tensile strength and fatigue
resistance, which could make them suitable for certain safety-critical applications
in the automotive industry. However, the MC-DC V3 variant experienced
challenges in crash testing scenarios, highlighting the need for further process
optimization and a deeper investigation into the relationship between
microstructure and mechanical performance under dynamic stress conditions.
While MC-DC casting may reduce reliance on chemical grain refiners, suggesting
a possible greener production approach, further research is necessary to fully
understand its impact on supply chains and production costs. Overall, the study
suggests that MC-DC casting has potential as a promising innovation in
aluminium alloy production, with opportunities to enhance efficiency and
sustainability in specific applications.Engineering and Physical Sciences Research Council (EPSRC) and Constelliu
Exploring strength exercise prescription and its dose in rheumatoid arthritis
Get PDFThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonRheumatoid arthritis (RA) is a significant global burden. It causes pain and disability and has significant
socio-economic implications. Non-pharmacological interventions are commonly prescribed to
mitigate the impact of the disease. Strengthening exercise, supported by evidence from randomised
controlled trials (RCTs), has gained wider acceptance. The National Institute for Health and Care
Excellence (NICE) recommends strengthening exercise for managing the functional impairments
associated with the disease. Whilst modest benefits have been demonstrated, uncertainties persist
regarding the optimal dosage. This thesis endeavours to enhance our understanding of the
prescription of strengthening exercise and its dose in RA through three original interrelated studies.
Study one systematically reviewed contemporary RCTs where strengthening exercise was a main
component of the intervention being evaluated. How dose of strengthening exercise was determined
for the trial intervention was investigated. The majority of included RCTs did not: (1) Report piloting
the intervention and its dose prior to conducting the RCT and (2) Cite any evidence underpinning the
dose of strengthening exercise prescribed for participants taking part in the trial. Moreover, when
evidence was cited, it varied in quality. Often the dose used or recommended in the underpinning
evidence was inconsistently applied in the intervention being evaluated by the RCT. Frequently, the
underpinning evidence was not directly applicable to individuals living with RA. The findings of this
review cast doubt on whether dose of strengthening exercise is optimised for individuals with RA in
RCTS.
Study two investigated the dose in hand strengthening exercise prescribed and completed during the
Strengthening And Stretching For Rheumatoid Arthritis of the Hand (SARAH) multicentre RCT. The
study utilised the area under the curve (AUC) method to quantify the overall dosage of hand
strengthening exercise prescribed across the five face-to-face exercise sessions. General estimating
equation (GEE) multiple regression analysis was then employed to determine: (1) The relationship
between prescribed overall dose and key outcomes (overall hand function and grip strength) and (2)
What factors were associated with the overall dose prescribed. Results indicated that participants who
were prescribed a higher overall dose of hand strengthening exercise exhibited better overall hand
function and grip strength. Factors that influenced overall dose prescribed included the professional
background of the therapist (i.e. occupational therapist or physiotherapist) and baseline participant
characteristics including metacarpophalangeal joint deformity, number of swollen wrist/hand joints,
grip strength, participant mood, and confidence to exercise without fear of making symptoms worse. Study three employed judgement analysis (JA) to evaluate how occupational therapists and
physiotherapists (therapists) judge what intensity (a key dose parameter) of hand strengthening
exercise to prescribe an individual with pain and dysfunction of the hand associated with RA. A
modified Delphi process involving therapists experienced in managing hand impairments associated
with RA was used to prioritise the key clinical cues included in the case scenarios. Therapists based in
the United Kingdom (UK) were then invited to assess a set of sixty-nine case scenarios (54 + 15 repeats)
via an online platform. Their judgements on prescribed intensity of hand strengthening exercise were
explored using multiple regression analysis. Results indicated all therapists reduced the intensity of
the exercise as the severity of the clinical cue increased. The cues that influenced therapists the most
included: (1) Patient’s pain performing the exercise, (2) Disease activity and (3) Average pain over the
preceding week, (4) Hand range of movement, (5) Ulnar drift and (6) Patient grip strength. Sub-analysis
employing the Cochran-Weiss-Shanteau (CWS) index of expertise identified therapists who were more
consistent in their prescribing judgements relied on fewer clinical cues (1-3), implying a form of
pattern recognition may be associated with their prescribing judgements.
In summary, dose is a crucial aspect of therapeutic exercise prescription. These studies provide new
insights into prescribing and dosing of strengthening exercises for RA in both clinical trials and practice.
Based on these findings, this thesis proposes several future research directions. First, the issues
identified in study one may not be limited to strengthening exercises and RA. Investigating whether
similar issues exist in RCTs evaluating other therapeutic exercise-based interventions used to manage
other musculoskeletal disorders is urgently needed to understand whether dose is sufficiently
optimised in rehabilitation research more broadly. Second, to actualise the full potential of
therapeutic exercise-based interventions, alternative methods for optimising dose warrant
investigation. Dose escalation methodology may offer healthcare researchers a viable alternative to
employing past research, which for strengthening exercise in RA, is often low quality and not
applicable to the clinical population of interest. Third, further exploration around how healthcare
professionals optimise dose of exercise-based interventions at the point of contact is essential for
optimising exercise prescription in clinical practice.Brunel University London, the National Institute for Health Research Applied Research Collaboration Oxford and Thames Valley at Oxford Health NHS Foundation Trust, and the NIHR Biomedical Research Centre, Oxfor
Class Imbalance Wafer Defect Pattern Recognition Based on Shared-Database Decentralized Federated Learning Framework
Get PDFIn this article, a novel shared-database decentralized federated learning (SDeceFL) framework is developed for wafer defect pattern recognition (DPR). Specifically, a differential privacy shared-database strategy is proposed to overcome the interclass heterogeneity problem of different clients and enhance data privacy. A deformable convolutional autoencoder (DCAE) is designed for data augmentation for handling class imbalance. The vision transformer (ViT) is employed for wafer DPR. The proposed DCAE-ViT-SDeceFL framework is validated on three public datasets (e.g., WM-811K, NEU-CLS-64, and CIFAR-100). The experimental results show the superiority of the SDeceFL framework over Ratio Loss-FedAvg, MOON, FedNH, BalanceFL, federated averaging (FedAvg), DeceFL, and swarm learning (SL). Compared with some deep learning methods, experimental results exhibit the effectiveness of the proposed DCAE-ViT-SDeceFL method for wafer DPR on WM-811K.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62273264 and 61933007);
Brunel Research Initiative and Enterprise Fund (BRIEF) at Brunel University London;
10.13039/501100001809-Royal Society of U.K.;
Alexander von Humboldt Foundation of Germany
Complete convergence for weighted sums of m-widely acceptable random variables under sub-linear expectations
Get PDFMathematics subject classification (2020): 60F15.In this paper, under the assumption of the existence of Choquet integrals, the complete convergence properties for weighted sums of m-widely acceptable random variables in sub-linear expectation space are investigated. The results obtained in the paper generalize the corresponding ones for some dependent sequences.The work is supported by National Social Science Fundation (Grant No. 21BTJ040),Project of Outstanding Young People in University of Anhui Province (No. 2023AH020037) and International Joint Research Center of Simulation and Control for Population Ecology of Yangtze River in Anhui (No. SLXY2024A001)
LONELINESS TRANSITIONS AMONG MINORITY ETHNIC AND LGB POPULATIONS IN THE UK
Get PDFLoneliness has been identified as a major public health problem. Although there is a substantial body of research about loneliness in older adults in the UK, there is a significant evidence gap reporting experiences of loneliness among older people from ethnic minorities and those who identify as lesbian, gay, or bisexual (LGB). We focus upon the experiences of loneliness for adults aged 50+, from LGB and minority ethnic communities. Using waves 9-12 of the annual UK Household Longitudinal Study (UKHLS/Understanding Society) we measured loneliness using the three-item UCLA scale with a score of 6+ out of 9 defining loneliness. 7,646 respondents completed the loneliness measure at each wave. 1.7% of participants identified as LGB and 4.3% as Asian, 2.5% as black and 1.4% as mixed /other ethnicity. We grouped respondents into three categories: (a) consistently lonely; (b) consistently not lonely and (c) fluctuating loneliness. A higher proportion of LGB respondents were consistently lonely (16.4% vs 9.2%), compared to heterosexual respondents. Respondents from black (14.1%), Asian (11.2%) and other ethnic minorities (17.5%) were more likely to be consistently lonely in comparison to white respondents (8.9%). Shortcomings in data available on these groups of interest limit our analytical power to examine the importance of micro, meso and macro-level risk factors. Preliminary findings suggest that socio-demographic predictors for fluctuating or persistent loneliness differ in our groups of interest in comparison with white or heterosexual respondents. The higher level of persistent loneliness in the two groups has potential implications for their health and wellbeing
Neural network–based transfer learning to improve stiffness modeling of industrial robots with small experimental data sets
Get PDFStiffness modeling is an essential subject for the composition of robot control. Accurate stiffness modeling is helpful for improving the control accuracy of industrial robots, particularly under dynamic load circumstances. The classic virtual joint modeling (VJM) method is challenging in predicting the deformation of the end-effector throughout the full workspace due to the nonlinear deformation of the robot joint and its serial articulated structure. This paper proposes a full-space stiffness modeling method for robots based on the integration of a multi-layer perceptual (MLP) model and VJM. To provide enough training data for the MLP model, VJM is used to build a stiffness model with a small set of experimental data to generate 106,400 training data. A model-based transfer learning approach is proposed to improve the model’s accuracy and generalization regarding the difference between generated training data and actual experimental data. The VJM stiffness model is compared with the MLP stiffness model and the existing CNN-based transfer learning model based on the same experimental data. Considering the deformation prediction in the three directions in Cartesian space, the mean absolute error, standard deviation, and maximum error of the MLP model are decreased by at least 24.90%, 14.20%, and 8.50%, respectively, than the VJM. These prediction results demonstrate that the proposed modeling technique can significantly increase the accuracy of robot stiffness modeling, which is essential for position compensation in precise motion control of robots under dynamic load.The study was funded by the Ministry of Education of the People’s Republic of China (CN) (HZKY20220104) and the Brunel University London (12495103)
Multimorbidity clusters and their associations with health-related quality of life in two UK cohorts
Get PDFData availability:
The data that support these findings are available from UK Biobank and the UK Data service, subject to successful registration and application processes. Access to data from UK Biobank can be requested via the UK Biobank Access Management System https://www.ukbiobank.ac.uk/. Access to UKHLS data can be requested via UK Data Service https://ukdataservice.ac.uk/.Supplementary Information is available online at: https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-024-03811-3#Sec24 .Background:
Identifying clusters of multiple long-term conditions (MLTCs), also known as multimorbidity, and their associated burden may facilitate the development of effective and cost-effective targeted healthcare strategies. This study aimed to identify clusters of MLTCs and their associations with long-term health-related quality of life (HRQoL) in two UK population-based cohorts.
Methods:
Age-stratified clusters of MLTCs were identified at baseline in UK Biobank (n = 502,363, 54.6% female) and UKHLS (n = 49,186, 54.8% female) using latent class analysis (LCA). LCA was applied to people who self-reported ≥ 2 LTCs (from n = 43 LTCs [UK Biobank], n = 13 LTCs [UKHLS]) at baseline, across four age-strata: 18–36, 37–54, 55–73, and 74 + years. Associations between MLTC clusters and HRQoL were investigated using tobit regression and compared to associations between MLTC counts and HRQoL. For HRQoL, we extracted EQ-5D index data from UK Biobank. In UKHLS, SF-12 data were extracted and mapped to EQ-5D index scores using a standard preference-based algorithm. HRQoL data were collected at median 5 (UKHLS) and 10 (UK Biobank) years follow-up. Analyses were adjusted for available sociodemographic and lifestyle covariates.
Results:
LCA identified 9 MLTC clusters in UK Biobank and 15 MLTC clusters in UKHLS. Clusters centred around pulmonary and cardiometabolic LTCs were common across all age groups. Hypertension was prominent across clusters in all ages, while depression featured in younger groups and painful conditions/arthritis were common in clusters from middle-age onwards. MLTC clusters showed different associations with HRQoL. In UK Biobank, clusters with high prevalence of painful conditions were consistently associated with the largest deficits in HRQoL. In UKHLS, clusters of cardiometabolic disease had the lowest HRQoL. Notably, negative associations between MLTC clusters containing painful conditions and HRQoL remained significant even after adjusting for number of LTCs.
Conclusions:
While higher LTC counts remain important, we have shown that MLTC cluster types also have an impact on HRQoL. Health service delivery planning and future intervention design and risk assessment of people with MLTCs should consider both LTC counts and MLTC clusters to better meet the needs of specific populations.This study undertaken as part of the PERFORM programme and funded by the NIHR (Award ID: NIHR202020)]. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. KJ is part-funded by the NIHR Applied Research Collaboration West Midlands (ARC-WM). SD’s time is supported by the NIHR Applied Research Collaboration South West Peninsula (PenARC). SS is NIHR Senior Investigator and SS and RE was supported by the Leicester Biomedical Research Centre (BRC)
Evolution of colistin resistance in Acinetobacter baumannii and disrupting the colistin resistance mechanisms
Get PDFThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe emergence of antibiotic resistance is a global threat, rendering our reservoir of antibiotics
ineffective against many bacterial pathogens. In 2019, 4.95 million people died with an
antibiotic-resistant associated infection. One major contributor to this crisis is Acinetobacter
baumannii, a Gram-negative multi-drug resistant (MDR) pathogen listed by the World Health
Organisations (WHO) as a priority for novel therapeutic interventions.
This thesis explores innovative approaches against MDR A. baumannii, focusing on the
therapeutic properties of phytochemicals and plant extracts, more specifically kaempferol and
tormentil. Kaempferol, a phytochemical derived from capers and strawberries, in combination
with colistin, reduces the growth of A. baumannii and inhibits biofilm formation when used
on its own. Additionally, kaempferol disrupts iron homeostasis, resulting in increased reactive
oxygen species under colistin stress, leading to bacterial death. Similarly, tormentil, a plant
used in traditional Irish folklore medicine for treating burn wounds, and its constituents exhibit
significant antimicrobial and antibiofilm activity against A. baumannii. Our mechanistic
studies reveal that these extracts also impact bacterial iron homeostasis. These findings
demonstrate the potential of iron-chelating compounds as colistin potentiators or standalone
antimicrobials against MDR A. baumannii.
Additionally, we investigate the fitness and virulence costs associated with colistin
resistance. Our laboratory evolved colistin-resistant mutants (CRMs) show varied growth rates
in the presence of colistin and slow growth rates in the absence. The CRMs also show an
increased biofilm formation and reduced virulence, illustrating the trade-offs of evolved
colistin resistance. In vivo analysis of known and novel mutations in PmrB revealed structural
changes that may enhance kinase activity and mediate colistin resistance.
These findings uncover metabolic vulnerabilities in A. baumannii, suggesting new
strategies to enhance colistin efficacy through phytochemicals and plant extracts and further
our knowledge in understanding the trade-offs of evolved resistance in A. baumannii.
Together, these insights can contribute to the design and development of more effective
treatments against MDR A. baumannii
An evaluation of community health care service in Ghana: A case of the Community-Based Health and Planning Service (CHPS) compound in Ghana
Get PDFThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonBackground: Ghana implemented the Community-based Health Planning Services (CHPS) as
a primary healthcare initiative designed to provide essential health services to underserved
rural communities in Ghana. To date there is paucity of evidence on the effectiveness of the
CHPS initiative in Ghana. In addition to the limited evidence on the initiative’s effectiveness,
there is also limited understanding on the determinants of the positioning of the CHPS
compounds in Ghana. Such knowledge is critical to inform the initiative’s continuous
operation and improvement. The general aim of the study is to evaluate the effectiveness and
implementation of primary health service centres in Ghana, to inform policy making and
enhance health service delivery through optimised location, positioning, and operational
efficiency, along the CHPS Zones.
Methods: A review of 39 studies identified knowledge gaps on CHPS's effectiveness and
influencing factors. An Interrupted Time Series Analysis (ITSA) assessed CHPS effectiveness
using metrics such as Family Planning (FP) visits, Antenatal Care (ANC) visits, Maternal
Deliveries, and Outpatient Department (OPD) attendance. Secondary data from the Ghana
Health Service supported these analyses. Three Logistic Regression models examined factors
determining CHPS positioning, and a Generalized Linear Model assessed disease outbreak
distances relative to CHPS facilities across 216 districts. Additionally, a Discrete Event
Simulation modelled CHPS operations to suggest service delivery improvements.
Results: The ITSA indicated significant improvements in maternal and child health outcomes,
particularly maternal deliveries and ANC visits, since 2016. However, OPD visit effectiveness
requires further strengthening. Analysis showed that out of 117 districts, 68 had at least one
CHPS facility within 8 km, but 83 did not meet the mandated threshold. Districts with no CHPS facilities were 12% more likely to be closer to disease outbreaks. Districts with 6-11 CHPS
facilities were farther from disease outbreaks, while those with over 11 facilities were closer
to outbreaks. Simulation results revealed lengthy wait times as a major challenge, suggesting
an increase in staff and assessment rooms to boost efficiency.
Conclusions: The study revealed that districts with CHPS facilities were more distanced from
disease hotspots compared to those without such facilities, underscoring the pivotal role of
primary healthcare in disease prevention and control. Additionally, the simulation of CHPS
operations highlighted significant issues related to lengthy wait times, which can adversely
affect healthcare demand and utilization. The findings advocate for interventions to
streamline patient flow and improve service delivery efficiency, emphasizing the importance
of staff training and flexible staffing schedules. The implications for policy are many-fold.
Firstly, there is a clear need for a strategic and equitable expansion of CHPS facilities across
Ghana, prioritizing underserved, and remote districts. Policymakers should consider a
strategic increase in the number of CHPS facilities to ensure they are adequately staffed,
equipped, and integrated into the community’s already existing healthcare system.
Moreover, continuous monitoring and assessment of these facilities are essential to maintain
their effectiveness and adapt to evolving healthcare needs.Ghana Scholarships Secretaria
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