A Virtual Construction Model of 4D planning in Road Project

Construction managers require innovative techniques to assist them in producing accurate planning tasks such as resource allocation and costing of activities because of unique characteristics of road construction industry. Visualisation technologies have potential to improve communications and coordination amongst the project stakeholders and to optimise onsite productivity through visual simulation of construction process and innovative planning approach. This research study introduces a framework of a 4D planning model for automatic generation of earthwork progress profiles and production cost profiles of a road section, and visualisation of the construction process throughout earthwork operations. The framework is designed and developed by integrating road design data, quantities of cut and fill sections, variable productivity data, algorithms for modelling terrain, and a road profile visualiser. The research details the model to recognise the framework outlined above and it generates progress profiles, cost histogram and a time location plan automatically for the earthwork activity. The model is validated with a real life case study in a road project and was found that the model to be beneficial in generating the terrain surfaces of progress, weekly cost profiles and a time location plan during the construction operations. The model is incorporated with the “variable” productivity data and soil characteristics for analysing with “what if” scenarios. The 4D planning model should assist to project planners and construction managers in producing efficient construction scheduling and resource plannin

Microwave characterization of low-loss FDM 3-D printed ABS with dielectric-filled metal-pipe rectangular waveguide spectroscopy

Over time the accuracy and speed by which a material can be characterized should improve. Today, the Nicolson-Ross-Weir (NRW) methodology represents a well-established method for extracting complex dielectric properties at microwave frequencies, with the use of a modern vector network analyzer. However, as will be seen, this approach suffers from three fundamental limitations to accuracy. Challenging NRW methods requires a methodical and robust investigation. To this end, using a dielectric-filled metal-pipe rectangular waveguide, five independent approaches are employed to accurately characterize the sample at the Fabry-Pérot resonance frequency (non-frequency dispersive modeling). In addition, manual Graphical and automated Renormalization spectroscopic approaches are introduced for the first time in waveguide. The results from these various modeling strategies are then compared and contrasted to NRW approaches. As a timely exemplar, 3-D printed acrylonitrile-butadiene-styrene (ABS) samples are characterized and the results compared with existing data available in the open literature. It is found that the various Fabry-Pérot resonance model results all agree with one another and validate the two new spectroscopic approaches; in so doing, exposing three limitations of the NRW methods. It is also shown that extracted dielectric properties for ABS differ from previously reported results and reasons for this are discussed. From measurement noise resilience analysis, a methodology is presented for determining the upper-bound signal-to-noise ratio for the vector network analyzer (not normally associated with such instrumentation). Finally, fused deposition modeling (FDM) 3-D printing results in a non-homogeneous sample that excites open-box mode resonances. This phenomenon is investigated for the first time, analytically and with various modeling strategies

Improving performance and the reliability of off-site pre-cast concrete production operations using simulation optimisation

The increased use of precast components in building and heavy civil engineering projects has led to the introduction of innovative management and scheduling systems to meet the demand for increased reliability, efficiency and cost reduction. The aim of this study is to develop an innovative crew allocation system that can efficiently allocate crews of workers to labour-intensive repetitive processes. The objective is to improve off-site pre-cast production operations using Multi-Layered Genetic Algorithms. The Multi-Layered concept emerged in response to the modelling requirements of different sets of labour inputs. As part of the techniques used in developing the Crew Allocation “SIM_Crew” System, a process mapping methodology is used to model the processes of precast concrete operations and to provide the framework and input required for simulation. Process simulation is then used to model and imitate all production processes, and Genetic Algorithms are embedded within the simulation model to provide a rapid and intelligent search. A Multi-Layered chromosome is used to store different sets of inputs such as crews working on different shifts and process priorities. A ‘Class Interval’ selection strategy is developed to improve the chance of selecting the most promising chromosomes for further investigation. Multi-Layered Dynamic crossover and mutation operators are developed to increase the randomness of the searching mechanism for solutions in the solution space. The results illustrate that adopting different combinations of crews of workers has a substantial impact on the labour allocation cost and this should lead to increased efficiency and lower production cost. In addition, the results of the simulation show that minimum throughput time, minimum process-waiting time and optimal resource utilisation profiles can be achieved when compared to a real-life case study

Lack Evidence Between CTLA-4 Gene Polymorphisms Among Rheumatoid Arthritis Patients

Rheumatoid arthritis is a chronic inflammatory disorder that typically affects the small joints in hands and feet. Genes involved in T-cell regulation are potential candidates. Association to cytotoxic T-lymphocyte-associated-4 (CTLA-4) protein, a negative regulator of T-cell activation, has previously been described in Rheumatoid arthritis patients. In this study, our aim was to determine the role of CTLA-4 polymorphism among patients with Rheumatoid arthritis. A total of 120 Rheumatoid arthritis patients (69 males and 51 females) with an age mean ± SD (67.2000± 11.74133), family history (16 positive/ 104 negative), rheumatoid factor test (RF) (43 positive/ 77 negative), Anti-CCP antibody test (120 positive/ 0 negative), and 120 controls (46 males and 74 females) of Iraqis ethnicity with an age mean ± SD (31.6583± 11.51579). There was no significant difference between the groups (Rheumatoid arthritis patients and their control) (P = 0.478). And CTLA-4 gene polymorphism in each group was compared (AA, GG, AG). There is no difference between the CTLA-4 (SNP +49 A/G rs#231775) gene polymorphism among Rheumatoid arthritis patients and healthy people. Keywords: CTLA-4, Genotype, Rheumatoid arthritis, Genetic susceptibility, SN

Path integral duality modified propagators in spacetimes with constant curvature

The hypothesis of path integral duality provides a prescription to evaluate the propagator of a free, quantum scalar field in a given classical background, taking into account the existence of a fundamental length, say, the Planck length, \lp, in a {\it locally Lorentz invariant manner}. We use this prescription to evaluate the duality modified propagators in spacetimes with {\it constant curvature} (exactly in the case of one spacetime, and in the Gaussian approximation for another two), and show that: (i) the modified propagators are ultra violet finite, (ii) the modifications are {\it non-perturbative} in \lp, and (iii) \lp seems to behave like a `zero point length' of spacetime intervals such that \l = \l[\sigma^{2}(x,x')+ {\cal O}(1) \lp^2 \r], where $\sigma(x,x')$ is the geodesic distance between the two spacetime points $x$ and $x'$, and the angular brackets denote (a suitable) average over the quantum gravitational fluctuations. We briefly discuss the implications of our results.Comment: v1. 10 pages, no figures; v2. 11 pages, acknowledgments adde

Transitioning or tinkering at a net-zero economy? Introducing an assessment framework for industrial cluster decarbonisation in the United Kingdom

Decarbonising industrial clusters globally is crucial in combating climate change and is integral to the United Kingdom's ambition of achieving a net-zero economy by 2050. The absence of holistic frameworks that provide a nuanced understanding of the broad spectrum of mitigation options for decarbonising industrial clusters, coupled with a deficiency in real-world empirical evaluations, present a substantial barrier in realising set targets for reducing CO2 emissions. The increasing fragmentations in industrial decarbonisation frameworks further exacerbates the challenge of identifying the necessary and sufficient actions for achieving optimal industrial decarbonisation and net-zero transitioning. This paper proposes an assessment framework for industrial cluster decarbonisation and aims to address the existing gaps, particularly in the assessment of social, economic, and environmental impact of any deployed technology. Focusing on a wide range of technologies, sectoral strategies, and regional dynamics, the proposed framework is driven by specific key performance indicators and a comprehensive human and data-driven analytical approach that reflects descriptive, diagnostic, and prescriptive insights on the Teesside industrial cluster in the United Kingdom. Following the validation of the proposed assessment framework, empirical findings from 30 in-depth semi-structured interviews, two workshops, focus group meetings and the literature on industrial decarbonisation reveal that the framework recognises the complex interplay of technology and decision-making in the transition to net-zero of industrial clusters. The article concludes that the proposed assessment framework can assist stakeholders, policymakers, and researchers in assessing the impacts of energy transition, which is critical to policy design and decision-making while also contributing to achieving sustainable decarbonisation goals