Search results for: construction risk assessment model

Authors: Raghav Srivastava, Namrata Ramachandran

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Strong sustainability has been, by consensus, imagined as comprising economic and extra-economic variables and cannot be viewed merely in terms of a trade-off between the economic needs of today and the potential left for tomorrow. Specifically, the cultural as well the ecological impacts of development projects on the affected communities should be evaluated, in addition to the economic. In developing and densely populated economies such as India, energy intensive development is seen as a sine qua non – a necessary trade off with ecological conservation. Although social impact assessment has been included as an inalienable part of the Environmental Impact Assessment required to be conducted under Indian law, it seems that the same is unable to meet the ends it seeks to achieve. The dissociation between those bearing the costs of development, and those reaping its benefits, lies at the heart of this failure. This paper attempts to study the various cost–benefit relationships for these minority stakeholders using the proposed Nyamjang Chhu hydroelectric power plant in Tawang District of Arunachal Pradesh (in North-east India) as the chief object of study, and discusses whether the current model of sustainable development is truly sustainable, given the level of social dissociation and disintegration that occurs between affected communities and their environment. The economic allure of hydroelectric projects in the hilly regions of India very rarely results in a proper assessment of their ecological and social externalities. Examining the various issues that have been agitated in the course of litigation over the Nyamjang Chhu hydroelectric project, the authors argue that there is a pressing need to re-evaluate the current Indian model of sustainable development going forward.

Keywords: hydroelectric power, socio-cultural dissociation, sustainable development, trade offs

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Authors: Kristina Sutiene, Lina Dapkute

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The paper investigates the current demographic trends that exert the sustainability of pension systems in most EU regions. Several drivers usually compose the demographic challenge, coming from the structure and trends of population in the country. As the case of research, three main variables of demographic risk in Lithuania have been singled out and have been used in making up the analysis. Over the last two decades, the country has presented a peculiar demographic situation characterized by pessimistic fertility trends, negative net migration rate and rising life expectancy that make the significant changes in labor-age population. This study, therefore, sets out to assess the relative impact of these risk factors both individually and in aggregate, while assuming economic trends to evolve historically. The evidence is presented using data of pension funds that operate in Lithuania and are financed by defined-contribution plans. To achieve this goal, the discrete-time pension fund’s value model is developed that reflects main operational modalities: contribution income from current participants and new entrants, pension disbursement and administrative expenses; it also fluctuates based on returns from investment activity. Age-structured Leslie population dynamics model has been integrated into the main model to describe the dynamics of fertility, migration and mortality rates upon age. Validation has concluded that Leslie model adequately fits the current population trends in Lithuania. The elasticity of pension system is examined using Loimaranta efficiency as a measure for comparison of plausible long-term developments of demographic risks. With respect to the research question, it was found that demographic risks have different levels of influence on future value of aggregated pension funds: The fertility rates have the highest importance, while mortality rates give only a minor impact. Further studies regarding the role of trying out different economic scenarios in the integrated model would be worthwhile.

Keywords: asset liability modelling, Leslie model, pension funds, population dynamics

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Authors: Surya Prasad Sharma, Suyash Katdare, Syed Ainul Hussain

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Human-induced factors contributed to the population decline of crocodylians in India which became evident by the mid-20th century when authorities forewarned the extinction risk for the crocodile and proposed regulation in the crocodile trade. The proposed action led to the enactment of national and international wildlife regulations to prohibit the trade-in of crocodile skins and parts. Subsequently, conservation translocation programs were initiated to restore the species in the wild through a 'head-start' approach. In India, the crocodile conservation program, which began in the early 1970s, has been one of India's longest-running conservation initiatives. The gharial (Gavialis gangeticus) population has benefitted, and the gharial number increased rapidly owing to these efforts. The immediate risk of extinction was averted as the gharial has recovered due to decades-long cumulative conservation efforts, the consideration of the genetic for monitoring the recovery of the recovered populations is still lacking. Hence, we assessed the genetic diversity of the Girwa gharial population in India using six polymorphic nuclear microsatellites loci and mitochondrial control region. The number of alleles per loci ranged between 2 to 5, and the allelic richness (Ar) was 2.67 ± 0.49, and the observed (Ho) and expected (He) heterozygosities were 0.42 ± 0.08 and 0.42 ± 0.09, respectively. The M-ratio yielded a value of (0.41 ± 0.16) lower than critical M, suggesting a genetic bottleneck in the Girwa population. We observed more mitochondrial control region haplotypes in the Girwa population than previously reported in the largest gharial population in the Chambal River. Overall, our study indicates that genetic diversity remains low despite the recovery in the Girwa population. Hence, we recommend a range-wide genetic assessment of gharial populations using high-throughput techniques to identify the source population and plan future translocation programs.

Keywords: conservation translocation, recovery, crocodile, bottleneck

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Authors: Mohammadreza Salek Faramarzi, Touraj Taghikhany

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In this paper, seismic fragility assessment of a recently developed hybrid structural system, known as the strongback system (SBS) is investigated. In this system, to mitigate the occurrence of the soft-story mechanism and improve the distribution of story drifts over the height of the structure, an elastic vertical truss is formed. The strengthened members of the braced span are designed to remain substantially elastic during levels of excitation where soft-story mechanisms are likely to occur and impose a nearly uniform story drift distribution. Due to the distinctive characteristics of near-field ground motions, it seems to be necessary to study the effect of these records on seismic performance of the SBS. To this end, a set of 56 near-field ground motion records suggested by FEMA P695 methodology is used. For fragility assessment, nonlinear dynamic analyses are carried out in OpenSEES based on the recommended procedure in HAZUS technical manual. Four damage states including slight, moderate, extensive, and complete damage (collapse) are considered. To evaluate each damage state, inter-story drift ratio and floor acceleration are implemented as engineering demand parameters. Further, to extend the evaluation of the collapse state of the system, a different collapse criterion suggested in FEMA P695 is applied. It is concluded that SBS can significantly increase the collapse capacity and consequently decrease the collapse risk of the structure during its life time. Comparing the observing mean annual frequency (MAF) of exceedance of each damage state against the allowable values presented in performance-based design methods, it is found that using the elastic vertical truss, improves the structural response effectively.

Keywords: IDA, near-fault, probabilistic performance assessment, seismic fragility, strongback system, uncertainty

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Authors: Soheila Sadeghi

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In construction projects, predicting project performance metrics accurately is essential for effective management and successful delivery. However, conventional methods often depend on fixed baseline plans, disregarding the evolving nature of project progress and external influences. To address this issue, we introduce a distinct approach based on machine learning to forecast key performance indicators, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category within an urban road reconstruction project. Our proposed model leverages time series forecasting techniques, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance by analyzing historical data and project progress. Additionally, the model incorporates external factors, including weather patterns and resource availability, as features to improve forecast accuracy. By harnessing the predictive capabilities of machine learning, our performance forecasting model enables project managers to proactively identify potential deviations from the baseline plan and take timely corrective measures. To validate the effectiveness of the proposed approach, we conduct a case study on an urban road reconstruction project, comparing the model's predictions with actual project performance data. The outcomes of this research contribute to the advancement of project management practices in the construction industry by providing a data-driven solution for enhancing project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, schedule variance, earned value management

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Authors: Sameh Shahin, Nannang Arrys

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Optimizing pit slope stability and reducing strip ratio of a mining operation are two key tasks in geotechnical engineering. With a growing demand for minerals and an increasing cost associated with extraction, companies are constantly re-evaluating the viability of mineral deposits and challenging their geological understanding. Within Rio Tinto Iron Ore, the Structural Geology (SG) team investigate and collect critical data, such as point based orientations, mapping and geological inferences from adjacent pits to re-model deposits where previous interpretations have failed to account for structurally controlled slope failures. Utilizing innovative data collection methods and data-driven investigation, SG aims to address the root causes of slope instability. Committing to a resource grid drill campaign as the primary source of data collection will often bias data collection to a specific orientation and significantly reduce the capability to identify and qualify complexity. Consequently, these limitations make it difficult to construct a realistic and coherent structural model that identifies adverse structural domains. Without the consideration of complexity and the capability of capturing these structural domains, mining operations run the risk of inadequately designed slopes that may fail and potentially harm people. Regional structural trends have been considered in conjunction with surface and in-pit mapping data to model multi-batter fold structures that were absent from previous iterations of the structural model. The risk is evident in newly identified dip-slope and rock-mass controlled sectors of the geotechnical design rather than a ubiquitous dip-slope sector across the pit. The reward is two-fold: 1) providing sectors of rock-mass controlled design in previously interpreted structurally controlled domains and 2) the opportunity to optimize the slope angle for mineral recovery and reduced strip ratio. Furthermore, a resulting high confidence model with structures and geometries that can account for historic slope instabilities in structurally controlled domains where design assumptions failed.

Keywords: structural geology, geotechnical design, optimization, slope stability, risk mitigation

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Authors: Mikhail V. Khachaturyan

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The article analyzes problems of improving the management systems of the ownership risks in the conditions of the transformation of the Russian economy. Among the main sources of threats business owners should highlight is the inefficiency of the implementation of business models and interaction with hired managers. In this context, it is particularly important to analyze the relationship of business models and ownership risks. The analysis of this problem appears to be relevant for a number of reasons: Firstly, the increased risk appetite of the owner directly affects the business model and the composition of his holdings; secondly, owners with significant stakes in the company are factors in the formation of particular types of risks for owners, for which relations have a significant influence on a firm's competitiveness and ultimately determines its survival; and thirdly, inefficient system of management ownership of risk is one of the main causes of mass bankruptcies, which significantly affects the stable operation of the economy as a whole. The separation of the processes of possession, disposal and use in modern organizations is the cause of not only problems in the process of interaction between the owner and managers in managing the organization as a whole, but also the asymmetric information about the kinds and forms of the main risks. Managers tend to avoid risky projects, inhibit the diversification of the organization's assets, while owners can insist on the development of such projects, with the aim not only of creating new values for themselves and consumers, but also increasing the value of the company as a result of increasing capital. In terms of separating ownership and management, evaluation of projects by the ratio of risk-yield requires preservation of the influence of the owner on the process of development and making management decisions. It is obvious that without a clearly structured system of participation of the owner in managing the risks of their business, further development is hopeless. In modern conditions of forming a risk management system, owners are compelled to compromise between the desire to increase the organization's ability to produce new value, and, consequently, increase its cost due to the implementation of risky projects and the need to tolerate the cost of lost opportunities of risk diversification. Improving the effectiveness of the management of ownership risks may also contribute to the revitalization of creditors on implementation claims to inefficient owners, which ultimately will contribute to the efficiency models of ownership control to exclude variants of insolvency. It is obvious that in modern conditions, the success of the model of the ownership of risk management and audit is largely determined by the ability and willingness of the owner to find a compromise between potential opportunities for expanding the firm's ability to create new value through risk and maintaining the current level of new value creation and an acceptable level of risk through the use of models of diversification.

Keywords: improving, ownership risks, problem, Russia

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Authors: Anthony R. Townsend, Robyn L. Fasser

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This research project provides an interpretative phenomenological analysis of a proposed conceptual model of parenting ability that has been designed to offer recommendations to guide intervention in child custody evaluations in South Africa. A recent review of the literature on child custody evaluations reveals that while there have been significant and valuable shifts in the capacity of the legal system aided by mental health professionals in understanding children and family dynamics, there remains a conceptual gap regarding the nature of parenting ability. With a view to addressing this paucity of a theoretical basis for considering parenting ability, this research project reviews a dimensional model for the assessment of parenting ability by conceiving parenting ability as a combination of good parenting and parental fitness. This model serves as a conceptual framework to guide child-custody evaluation and refine intervention in such cases to better meet the best interests of the child in a manner that bridges the professional gap between parties, legal entities, and mental health professionals. Using a model of good parenting as a point of theoretical departure, this model incorporates both intra-psychic and interpersonal attributes and behaviours of parents to form an impression of parenting ability and identify areas for potential enhancement. This research, therefore, hopes to achieve the following: (1) to provide nuanced descriptions of parents’ parenting ability; (2) to describe parents’ parenting potential; (3) to provide a parenting assessment tool for investigators in forensic family matters that will enable more useful recommendations and interventions; (4) to develop a language of consensus for investigators, attorneys, judges and parents, in forensic family matters, as to what comprises parenting ability and how this can be assessed; and (5) that all of the aforementioned will serve to advance the best interests of the children involved in such litigious matters. The evaluative promise and post-assessment prospects of this model are illustrated through three interlinking data sets: (1) the results of interviews with South African psychologists about the model, (2) retrospective analysis of care and contact evaluation reports using the model to determine if different conclusions or more specific recommendations are generated with its use and (3) the results of an interview with a psychologist who piloted this model by using it in care and contact evaluation.

Keywords: alienation, attachment, best interests of the child, care and contact evaluation, children’s act (38 of 2005), child custody evaluation, civil forensics, gatekeeping, good parenting, good-enough parenting, health professions council of South Africa, family law, forensic mental healthcare practitioners, parental fitness, parenting ability, parent management training, parenting plan, problem-determined system, psychotherapy, support of other child-parent relationship, voice of the child

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Authors: Elif D. Oguz Erkal, David Krackhardt, Erica Cochran-Hameen

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Even though social network analysis (SNA) is an abundantly studied concept for many organizations and industries, a clear SNA approach to the project teams has not yet been adopted by the construction industry. The main challenges for performing SNA in construction and the apparent reason for this gap is the unique and complex structure of each construction project, the comparatively high circulation of project team members/contributing parties and the variety of authentic problems for each project. Additionally, there are stakeholders from a variety of professional backgrounds collaborating in a high-stress environment fueled by time and cost constraints. Within this case study on Project RE, a design & build project performed at the Urban Design Build Studio of Carnegie Mellon University, social network analysis of the project design team will be performed with the main goal of applying social network theory to construction project environments. The research objective is to determine a correlation between the network of how individuals relate to each other on one’s perception of their own professional strengths and weaknesses and the communication patterns within the team and the group dynamics. Data is collected through a survey performed over four rounds conducted monthly, detailed follow-up interviews and constant observations to assess the natural alteration in the network with the effect of time. The data collected is processed by the means of network analytics and in the light of the qualitative data collected with observations and individual interviews. This paper presents the full ethnography of this construction design team of fourteen architecture students based on an elaborate social network data analysis over time. This study is expected to be used as an initial step to perform a refined, targeted and large-scale social network data collection in construction projects in order to deduce the impacts of social networks on project performance and suggest better collaboration structures for construction project teams henceforth.

Keywords: construction design teams, construction project management, social network analysis, team collaboration, network analytics

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Authors: Amir Reza Heydari, Yaser Jenab

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Coronary artery disease, a common cardiovascular disease, is attributed to the accumulation of cholesterol-based plaques in the coronary arteries, leading to atherosclerosis. This disease is associated with risk factors such as smoking, hypertension, diabetes, and elevated cholesterol levels, contributing to severe clinical consequences, including acute coronary syndromes and myocardial infarction. Treatment approaches such as from lifestyle interventions to surgical procedures like percutaneous coronary intervention and coronary artery bypass surgery. These interventions often employ stents, including bare-metal stents (BMS), drug-eluting stents (DES), and bioresorbable vascular scaffolds (BVS), each with its advantages and limitations. Computational tools have emerged as critical in optimizing stent designs and assessing their performance. The aim of this study is to provide an overview of the computational methods of studies based on the finite element (FE) method in the field of coronary stenting and discuss the potential for development and clinical application of stent devices. Additionally, the importance of assessing the ability of computational models is emphasized to represent real-world phenomena, supported by recent guidelines from the American Society of Mechanical Engineers (ASME). Validation processes proposed include comparing model performance with in vivo, ex-vivo, or in vitro data, alongside uncertainty quantification and sensitivity analysis. These methods can enhance the credibility and reliability of in silico simulations, ultimately aiding in the assessment of coronary stent designs in various clinical contexts.

Keywords: atherosclerosis, materials, restenosis, review, validation

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Authors: Shanza Akram, Sameen Toor, Heba Harb Abu Alkass, Zainab Abdulsalam Altaha, Sara Taha Abdulla, Saleem Imran

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Acute pulmonary embolism (PE) is a common disease and can be fatal. The clinical presentation is variable and nonspecific, making accurate diagnosis difficult. Testing patients with suspected acute PE has increased dramatically. However, the overuse of some tests, particularly CT and D-dimer measurement, may not improve care while potentially leading to patient harm and unnecessary expense. CTPA is the investigation of choice for PE. Its easy availability, accuracy and ability to provide alternative diagnosis has lowered the threshold for performing it, resulting in its overuse. Guidelines have recommended the use of clinical pretest probability tools such as ‘Wells score’ to assess risk of suspected PE. Unfortunately, implementation of guidelines in clinical practice is inconsistent. This has led to low risk patients being subjected to unnecessary imaging, exposure to radiation and possible contrast related complications. Aim: To study the diagnostic yield of CT PA, clinical pretest probability of patients according to wells score and to determine whether or not there was an overuse of CTPA in our service. Methods: CT scans done on patients with suspected P.E in our hospital from 1st January 2014 to 31st December 2014 were retrospectively reviewed. Medical records were reviewed to study demographics, clinical presentation, final diagnosis, and to establish if Wells score and D-Dimer were used correctly in predicting the probability of PE and the need for subsequent CTPA. Results: 100 patients (51male) underwent CT PA in the time period. Mean age was 57 years (24-91 years). Majority of patients presented with shortness of breath (52%). Other presenting symptoms included chest pain 34%, palpitations 6%, collapse 5% and haemoptysis 5%. D Dimer test was done in 69%. Overall Wells score was low (<2) in 28 %, moderate (>2 - < 6) in 47% and high (> 6) in 15% of patients. Wells score was documented in medical notes of only 20% patients. PE was confirmed in 12% (8 male) patients. 4 had bilateral PE’s. In high-risk group (Wells > 6) (n=15), there were 5 diagnosed PEs. In moderate risk group (Wells >2 - < 6) (n=47), there were 6 and in low risk group (Wells <2) (n=28), one case of PE was confirmed. CT scans negative for PE showed pleural effusion in 30, Consolidation in 20, atelactasis in 15 and pulmonary nodule in 4 patients. 31 scans were completely normal. Conclusion: Yield of CT for pulmonary embolism was low in our cohort at 12%. A significant number of our patients who underwent CT PA had low Wells score. This suggests that CT PA is over utilized in our institution. Wells score was poorly documented in medical notes. CT-PA was able to detect alternative pulmonary abnormalities explaining the patient's clinical presentation. CT-PA requires concomitant pretest clinical probability assessment to be an effective diagnostic tool for confirming or excluding PE. . Clinicians should use validated clinical prediction rules to estimate pretest probability in patients in whom acute PE is being considered. Combining Wells scores with clinical and laboratory assessment may reduce the need for CTPA.

Keywords: CT PA, D dimer, pulmonary embolism, wells score

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Authors: Rahmoune Abdelhaq

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Systemic risk is a key concern for central banks charged with safeguarding overall financial stability. In this work, we investigate how systemic risk is affected by the structure of the financial system. We construct banking systems that are composed of a number of banks that are connected by interbank linkages. We then vary the key parameters that define the structure of the financial system — including its level of capitalization, the degree to which banks are connected, the size of interbank exposures and the degree of concentration of the system — and analyses the influence of these parameters on the likelihood of contagious (knock-on) defaults. First, we find that the better-capitalized banks are, the more resilient is the banking system against contagious defaults and this effect is non-linear. Second, the effect of the degree of connectivity is non-monotonic, that is, initially a small increase in connectivity increases the contagion effect; but after a certain threshold value, connectivity improves the ability of a banking system to absorb shocks. Third, the size of interbank liabilities tends to increase the risk of knock-on default, even if banks hold capital against such exposures. Fourth, more concentrated banking systems are shown to be prone to larger systemic risk, all else equal. In an extension to the main analysis, we study how liquidity effects interact with banking structure to produce a greater chance of systemic breakdown. We finally consider how the risk of contagion might depend on the degree of asymmetry (tier) inherent in the structure of the banking system. A number of our results have important implications for public policy, which this paper also draws out. This paper also discusses why bank risk management is needed to get the optimal one.

Keywords: financial stability, contagion, liquidity risk, optimal risk

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Authors: Stephanie Wall, Guido Wimmers

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The construction and operation of buildings greatly contribute to environmental degradation through resource and energy consumption and greenhouse gas emissions. The design of the envelope system affects the environmental impact of a building in two major ways; 1) high thermal performance and air tightness can significantly reduce the operational energy of the building and 2) the material selection for the envelope largely impacts the embodied energy of the building. Life cycle assessment (LCA) is a scientific methodology that is used to systematically analyze the environmental load of processes or products, such as buildings, over their life. The paper will discuss the results of a comparative LCA of different envelope designs and the long-term monitoring of the Wood Innovation Research Lab (WIRL); a Passive House (PH), industrial building under construction in Prince George, Canada. The WIRL has a footprint of 30m x 30m on a concrete raft slab foundation and consists of shop space as well as a portion of the building that includes a two-story office/classroom space. The lab building goes beyond what was previously thought possible in regards to energy efficiency of industrial buildings in cold climates due to their large volume to surface ratio, small floor area, and high air change rate, and will be the first PH certified industrial building in Canada. These challenges were mitigated through the envelope design which utilizes solar gains while minimizing overheating, reduces thermal bridges with thick (570mm) prefabricated truss walls filled with blown in mineral wool insulation and a concrete slab and roof insulated with EPS rigid insulation. The envelope design results in lower operational and embodied energy when compared to buildings built to local codes or with steel. The LCA conducted using Athena Impact Estimator for Buildings identifies project specific hot spots as well illustrates that for high-efficiency buildings where the operational energy is relatively low; the embodied energy of the material selection becomes a significant design decision as it greatly impacts the overall environmental footprint of the building. The results of the LCA will be reinforced by long-term monitoring of the buildings envelope performance through the installation of temperature and humidity sensors throughout the floor slab, wall and roof panels and through detailed metering of the energy consumption. The data collected from the sensors will also be used to reinforce the results of hygrothermal analysis using WUFI®, a program used to verify the durability of the wall and roof panels. The WIRL provides an opportunity to showcase the use of wood in a high performance envelope of an industrial building and to emphasize the importance of considering the embodied energy of a material in the early stages of design. The results of the LCA will be of interest to leading researchers and scientists committed to finding sustainable solutions for new construction and high-performance buildings.

Keywords: high performance envelope, life cycle assessment, long term monitoring, passive house, prefabricated panels

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Authors: Skezeer John B. Paz, Ederlina G. Nocon

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Finding an optimal binary linear code is a central problem in coding theory. A binary linear code C = [n, k, d] is called optimal if there is no linear code with higher minimum distance d given the length n and the dimension k. There are bounds giving limits for the minimum distance d of a linear code of fixed length n and dimension k. The lower bound which can be taken by construction process tells that there is a known linear code having this minimum distance. The upper bound is given by theoretic results such as Griesmer bound. One way to find an optimal binary linear code is to make the lower bound of d equal to its higher bound. That is, to construct a binary linear code which achieves the highest possible value of its minimum distance d, given n and k. Some optimal binary linear codes were presented by Andries Brouwer in his published table on bounds of the minimum distance d of binary linear codes for 1 ≤ n ≤ 256 and k ≤ n. This was further improved by Markus Grassl by giving a detailed construction process for each code exhibiting the lower bound. In this paper, we construct new optimal binary linear codes by using some construction processes on existing binary linear codes. Particularly, we developed an algorithm applied to the codes already constructed to extend the list of optimal binary linear codes up to 257 ≤ n ≤ 300 for k ≤ 7.

Keywords: bounds of linear codes, Griesmer bound, construction of linear codes, optimal binary linear codes

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Authors: Oluwaseun Ijiwade, Chris Davison, Kelvin Gregory

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In Australia, like other parts of the world, the debate on how to enhance teachers using assessment data to inform teaching and learning of English as an Additional Language (EAL, Australia) or English as a Foreign Language (EFL, United States) have occupied the centre of academic scholarship. Traditionally, this approach was conceptualised as ‘Formative Assessment’ and, in recent times, ‘Assessment for Learning (AfL)’. The central problem is that teacher-made tests are limited in providing data that can inform teaching and learning due to variability of classroom assessments, which are hindered by teachers’ characteristics and assessment literacy. To address this concern, scholars in language education and testing have proposed a uniformed large-scale computer-based assessment program to meet the needs of teachers and promote AfL in language education. In Australia, for instance, the Victoria state government commissioned a large-scale project called 'Tools to Enhance Assessment Literacy (TEAL) for Teachers of English as an additional language'. As part of the TEAL project, a tool called ‘Reading and Vocabulary assessment for English as an Additional Language (RVEAL)’, as a diagnostic language assessment (DLA), was developed by language experts at the University of New South Wales for teachers in Victorian schools to guide EAL pedagogy in the classroom. Therefore, this study aims to provide qualitative evidence for understanding beliefs about the diagnostic language assessment (DLA) among EAL teachers in primary and secondary schools in Victoria, Australia. To realize this goal, this study raises the following questions: (a) How do teachers use large-scale assessment data for diagnostic purposes? (b) What skills do language teachers think are necessary for using assessment data for instruction in the classroom? and (c) What factors, if any, contribute to teachers’ beliefs about diagnostic assessment in a large-scale assessment? Semi-structured interview method was used to collect data from at least 15 professional teachers who were selected through a purposeful sampling. The findings from the resulting data analysis (thematic analysis) provide an understanding of teachers’ beliefs about DLA in a classroom context and identify how these beliefs are crystallised in language teachers. The discussion shows how the findings can be used to inform professional development processes for language teachers as well as informing important factor of teacher cognition in the pedagogic processes of language assessment. This, hopefully, will help test developers and testing organisations to align the outcome of this study with their test development processes to design assessment that can enhance AfL in language education.

Keywords: beliefs, diagnostic language assessment, English as an additional language, teacher cognition

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Authors: Bolormaa Dalanbayar, Batsaikhan Ulaankhuu, Bayarmaa Tsogtbaatar

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In this study, we surveyed employers and students to identify compliance between employers' needs and student self-assessment of skills. Employers' survey consisted of fifteen questions to determine employers' assessment of the knowledge and skills of graduates in heavy equipment repairer's programs from four TVET schools. We also compared a survey questionnaire with Liebherr brands' job duty requirements, which determines the training needs and qualification level of their new workers. The study shows more than 76% of employers assessed professional knowledge as sufficient, more than 47% of employers assessed vocational skills as sufficient and more than 43% of employers rated attitudes as sufficient. Therefore, we can state there is a skill mismatch between the employer's assessment and students' self-assessment.

Keywords: skill mismatch, employers needs, competence-based curriculum

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Authors: Y. Kim, H. Lee, M. Park, B. Lee

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Planning is understood as the determination of what has to be performed, how, in which sequence, when, what resources are needed, and their cost within the organization before execution. In most construction project, it is evident that the inherent nature of planning is dynamic, and initial planning is subject to be changed due to various uncertain conditions of construction project. Planners take a continuous revision process during the course of a project and until the very end of project. However, current practice lacks reliable, systematic tool for setting variance thresholds to determine when and what corrective actions to be taken. Rather it is heavily dependent on the level of experience and knowledge of the planner. Thus, this paper introduces a machine learning approach to evaluate project control threshold reliability incorporating project-specific data and presents a method to automate the process. The results have shown that the model improves the efficiency and accuracy of the monitoring process as an early warning.

Keywords: machine learning, project control, project progress monitoring, schedule

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Authors: Jonathan Iworiso

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Forecasting the equity premium out-of-sample is a major concern to researchers in finance and emerging markets. The quest for a superior model that can forecast the equity premium with significant economic gains has resulted in several controversies on the choice of variables and suitable techniques among scholars. This research focuses mainly on the application of Regression Training (RT) techniques to forecast monthly equity premium out-of-sample recursively with an expanding window method. A broad category of sophisticated regression models involving model complexity was employed. The RT models include Ridge, Forward-Backward (FOBA) Ridge, Least Absolute Shrinkage and Selection Operator (LASSO), Relaxed LASSO, Elastic Net, and Least Angle Regression were trained and used to forecast the equity premium out-of-sample. In this study, the empirical investigation of the RT models demonstrates significant evidence of equity premium predictability both statistically and economically relative to the benchmark historical average, delivering significant utility gains. They seek to provide meaningful economic information on mean-variance portfolio investment for investors who are timing the market to earn future gains at minimal risk. Thus, the forecasting models appeared to guarantee an investor in a market setting who optimally reallocates a monthly portfolio between equities and risk-free treasury bills using equity premium forecasts at minimal risk.

Keywords: regression training, out-of-sample forecasts, expanding window, statistical predictability, economic significance, utility gains

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Authors: Omid Giahi, Ebrahim Darvishi, Mahdi Akbarzadeh

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Introduction: Occupational low back pain (LBP) is one of the most prevalent work-related musculoskeletal disorders in which a lot of risk factors are involved that. The present study focuses on the relation between personal, psycho-social and occupational risk factors and LBP severity in industrial workers. Materials and Methods: This research was a case-control study which was conducted in Kurdistan province. 100 workers (Mean Age ± SD of 39.9 ± 10.45) with LBP were selected as the case group, and 100 workers (Mean Age ± SD of 37.2 ± 8.5) without LBP were assigned into the control group. All participants were selected from various industrial units, and they had similar occupational conditions. The required data including demographic information (BMI, smoking, alcohol, and family history), occupational (posture, mental workload (MWL), force, vibration and repetition), and psychosocial factors (stress, occupational satisfaction and security) of the participants were collected via consultation with occupational medicine specialists, interview, and the related questionnaires and also the NASA-TLX software and REBA worksheet. Chi-square test, logistic regression and structural equation modeling (SEM) were used to analyze the data. For analysis of data, IBM Statistics SPSS 24 and Mplus6 software have been used. Results: 114 (77%) of the individuals were male and 86 were (23%) female. Mean Career length of the Case Group and Control Group were 10.90 ± 5.92, 9.22 ± 4.24, respectively. The statistical analysis of the data revealed that there was a significant correlation between the Posture, Smoking, Stress, Satisfaction, and MWL with occupational LBP. The odds ratios (95% confidence intervals) derived from a logistic regression model were 2.7 (1.27-2.24) and 2.5 (2.26-5.17) and 3.22 (2.47-3.24) for Stress, MWL, and Posture, respectively. Also, the SEM analysis of the personal, psycho-social and occupational factors with LBP revealed that there was a significant correlation. Conclusion: All three broad categories of risk factors simultaneously increase the risk of occupational LBP in the workplace. But, the risks of Posture, Stress, and MWL have a major role in LBP severity. Therefore, prevention strategies for persons in jobs with high risks for LBP are required to decrease the risk of occupational LBP.

Keywords: industrial workers occupational, low back pain, occupational risk factors, psychosocial factors

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Authors: Yohanes Kristianto

Abstract:

The objective of this paper is to compose a sustainable supply chain that integrates product, process and networks design. An integrated life cycle assessment and techno-economic optimization is proposed that might deliver more economically feasible operations, minimizes environmental impacts and maximizes social contributions. Closed loop economy of the supply chain is achieved by reusing waste to be raw material of final products. Societal benefit is given by the supply chain by absorbing waste as source of raw material and opening new work opportunities. A case study of ethanol supply chain from rice straws is considered. The modeling results show that optimization within the scope of LCA is capable of minimizing both CO₂ emissions and energy and utility consumptions and thus enhancing raw materials utilization. Furthermore, the supply chain is capable of contributing to local economy through jobs creation. While the model is quite comprehensive, the future research recommendation on energy integration and global sustainability is proposed.

Keywords: life cycle assessment, techno-economic optimization, sustainable supply chains, closed loop economy

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Authors: Yegnanew A. Shiferaw

Abstract:

Background: commodity price volatility originating from excessive commodity price fluctuation has been a global problem especially after the recent financial crises. Volatility is a measure of risk or uncertainty in financial analysis. It plays a vital role in risk management, portfolio management, and pricing equity. Objectives: the core objective of this paper is to examine the relationship between the prices of agricultural commodities with oil price, gas price, coal price and exchange rate (USD/Rand). In addition, the paper tries to fit an appropriate model that best describes the log return price volatility and estimate Value-at-Risk and expected shortfall. Data and methods: the data used in this study are the daily returns of agricultural commodity prices from 02 January 2007 to 31st October 2016. The data sets consists of the daily returns of agricultural commodity prices namely: white maize, yellow maize, wheat, sunflower, soya, corn, and sorghum. The paper applies the three-state Markov-switching (MS) regression, the standard single-regime GARCH and the two regime Markov-switching GARCH (MS-GARCH) models. Results: to choose the best fit model, the log-likelihood function, Akaike information criterion (AIC), Bayesian information criterion (BIC) and deviance information criterion (DIC) are employed under three distributions for innovations. The results indicate that: (i) the price of agricultural commodities was found to be significantly associated with the price of coal, price of natural gas, price of oil and exchange rate, (ii) for all agricultural commodities except sunflower, k=3 had higher log-likelihood values and lower AIC and BIC values. Thus, the three-state MS regression model outperformed the two-state MS regression model (iii) MS-GARCH(1,1) with generalized error distribution (ged) innovation performs best for white maize and yellow maize; MS-GARCH(1,1) with student-t distribution (std) innovation performs better for sorghum; MS-gjrGARCH(1,1) with ged innovation performs better for wheat, sunflower and soya and MS-GARCH(1,1) with std innovation performs better for corn. In conclusion, this paper provided a practical guide for modelling agricultural commodity prices by MS regression and MS-GARCH processes. This paper can be good as a reference when facing modelling agricultural commodity price problems.

Keywords: commodity prices, MS-GARCH model, MS regression model, South Africa, volatility

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Authors: Abdessalem Abbassi, Ahlem Dakhlaoui, Lota D. Tamini

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This article analyses management of hydropower dams within two different industrial structures: monopolistic and oligopolistic; when hydroelectricity producers are risk averse and face demand uncertainty. In each type of market structure we determine the water release path in closed-loop equilibrium. We show how a monopoly can manage its hydropower dams by additional pumping or storage depending on the relative abundance of water between different regions to smooth the effect of uncertainty on electricity prices. In the oligopolistic case with symmetric rates of risk aversion, we determine the conditions under which the relative scarcity (abundance) of water in the dam of a hydroelectric operator can favor additional strategic pumping (storage) in its competitor’s dams. When there is asymmetry of the risk aversion coefficient, the firm’s hydroelectricity production increases as its competitor’s risk aversion increases, if and only if the average recharge speed of the competitor’s dam exceeds a certain threshold, which is an increasing function of its average water inflows.

Keywords: asymmetric risk aversion, closed-loop Cournot competition, electricity wholesale market, hydropower dams

Procedia PDF Downloads 354

Authors: Melaku Takele Abate, Abbi Lemma Wodajo, Adula Bekele Hunde

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This study aimed at exploring mathematics teachers' reactions, learning, school leaders’ support, and use of the Lesson Study for Transformative Assessment (LSforTA) program ideas in practice. The LSforTA program was new, and therefore, a local and grounded approach was needed to examine teachers’ knowledge and skills acquired using LSforTA. So, a design-based research approach was selected to evaluate and refine the LSforTA approach. The results showed that LSforTA increased teachers' knowledge and use of different levels of mathematics assessment tasks. The program positively affected teachers' practices of transformative assessment and enhanced their knowledge and skills in assessing students in a transformative way. The paper concludes how the LSforTA procedures were adapted in response to this evaluation and provides suggestions for future development and research.

Keywords: classroom assessment, feedback practices, lesson study, mathematics, design-based research

Procedia PDF Downloads 55

Authors: Christos E. Lampropoulos, Maria Konsta, Tamta Sirbilatze, Ifigenia Apostolou, Vicky Dradaki, Konstantina Panouria, Irini Dri, Christina Kordali, Vaggelis Lambas, Georgios Mavras

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Objectives: Full Mini Nutritional Assessment (MNA) questionnaire is one of the most useful tools in diagnosis of malnutrition in hospitalized patients, which is related to increased morbidity and mortality. The purpose of our study was to assess the nutritional status of elderly, hospitalized patients and examine the hypothesis that MNA may predict mortality and extension of hospitalization. Methods: One hundred fifty patients (78 men, 72 women, mean age 80±8.2) were included in this cross-sectional study. The following data were taken into account in analysis: anthropometric and laboratory data, physical activity (International Physical Activity Questionnaires, IPAQ), smoking status, dietary habits, cause and duration of current admission, medical history (co-morbidities, previous admissions). Primary endpoints were mortality (from admission until 6 months afterwards) and duration of admission. The latter was compared to national guidelines for closed consolidated medical expenses. Logistic regression and linear regression analysis were performed in order to identify independent predictors for mortality and extended hospitalization respectively. Results: According to MNA, nutrition was normal in 54/150 (36%) of patients, 46/150 (30.7%) of them were at risk of malnutrition and the rest 50/150 (33.3%) were malnourished. After performing multivariate logistic regression analysis we found that the odds of death decreased 20% per each unit increase of full MNA score (OR=0.8, 95% CI 0.74-0.89, p < 0.0001). Patients who admitted due to cancer were 23 times more likely to die, compared to those with infection (OR=23, 95% CI 3.8-141.6, p=0.001). Similarly, patients who admitted due to stroke were 7 times more likely to die (OR=7, 95% CI 1.4-34.5, p=0.02), while these with all other causes of admission were less likely (OR=0.2, 95% CI 0.06-0.8, p=0.03), compared to patients with infection. According to multivariate linear regression analysis, each increase of unit of full MNA, decreased the admission duration on average 0.3 days (b:-0.3, 95% CI -0.45 - -0.15, p < 0.0001). Patients admitted due to cancer had on average 6.8 days higher extension of hospitalization, compared to those admitted for infection (b:6.8, 95% CI 3.2-10.3, p < 0.0001). Conclusion: Mortality and extension of hospitalization is significantly increased in elderly, malnourished patients. Full MNA score is a useful diagnostic tool of malnutrition.

Keywords: duration of admission, malnutrition, mini nutritional assessment score, prognostic factors for mortality

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Authors: Benjamin A. Ha, Marco Morselli, Xinhui Paige Zhang, Elizabeth A. C. Heath-Heckman, Jonathan B. Puritz, David K. Jacobs

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Next-generation sequencing has enhanced the ability to acquire massive amounts of sequence data to address classic population genetic questions for non-model organisms. Targeted approaches allow for cost effective or more precise analyses of relevant sequences; although, many such techniques require a known genome and it can be costly to purchase probes from a company. This is challenging for non-model organisms with no published genome and can be expensive for large population genetic studies. Expressed exome capture sequencing (EecSeq) synthesizes probes in the lab from expressed mRNA, which is used to capture and sequence the coding regions of genomic DNA from a pooled suite of samples. A normalization step produces probes to recover transcripts from a wide range of expression levels. This approach offers low cost recovery of a broad range of genes in the genome. This research project expands on EecSeq to investigate if mRNA from one taxon may be used to capture relevant sequences from a series of increasingly less closely related taxa. For this purpose, we propose to use the endangered Northern Tidewater goby, Eucyclogobius newberryi, a non-model organism that inhabits California coastal lagoons. mRNA will be extracted from E. newberryi to create probes and capture exomes from eight other taxa, including the more at-risk Southern Tidewater goby, E. kristinae, and more divergent species. Captured exomes will be sequenced, analyzed bioinformatically and phylogenetically, then compared to previously generated phylogenies across this group of gobies. This will provide an assessment of the utility of the technique in cross-species studies and for analyzing low genetic variation within species as is the case for E. kristinae. This method has potential applications to provide economical ways to expand population genetic and evolutionary biology studies for non-model organisms.

Keywords: coastal lagoons, endangered species, non-model organism, target capture method

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Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu

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The present research is built on three major pillars, commencing by making some considerations on accident investigation methods and pointing out both defining aspects and differences between linear and non-linear analysis. The traditional linear focus on accident analysis describes accidents as a sequence of events, while the latest systemic models outline interdependencies between different factors and define the processes evolution related to a specific (normal) situation. Linear and non-linear accident analysis methods have specific limitations, so the second point of interest is mirrored by the aim to discover the drawbacks of systemic models which becomes a starting point for developing new directions to identify risks or data closer to the cause of incidents/accidents. Since communication represents a critical issue in the interaction of human factor and has been proved to be the answer of the problems made by possible breakdowns in different communication procedures, from this focus point, on the third pylon a new error-modeling instrument suitable for risk assessment/accident analysis will be elaborated.

Keywords: accident analysis, multi-factorial error modeling, risk, systemic methods

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Authors: Robert K. Hillyard, Jonathan Thomas, Brett A. Story

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Compressed Stabilized Earth Blocks (CSEB) are masonry units that combine soil, sand, stabilizer, and water under pressure to form an earth block. These CSEB’s offer a cost-effective building solution for remote construction, using local resources and labor to minimize transportation and material costs. However, CSEB’s, and earthen construction generally have not been widely adopted as standardized construction materials. One shortcoming is the difficulty in standardizing strength values of CSEB units and systems due to the inherent variations in mix design, including production compression. This research presents findings on compressive strengths of full-scale CSEB’s from 60 different mix designs as a function of the amount of cement, sand, soil, and water added to the mixture. The full-scale results are compared with CSEB cylinder cores.

Keywords: CSEB, compressive strength, earth construction, mix design

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Authors: A. Aljohani, D. Moore, D. D. Ahiaga-Dagbui

Abstract:

Cost overruns are endemic in the delivery of construction projects. The problem is global. It occurs irrespective of type and size of the project, its location, procurement method or client. The size of overruns can be as high as 200% in some cases. Projects thus unfortunately often make the news headlines, not for their immense socio-economic contribution to society, but for being poorly procured. In Saudi Arabia, two-thirds of construction projects are publicly procured by the Saudi government, which has been invested Billions of dollars in infrastructure projects each year as part of an ambitious strategic development agenda to shift from mainly oil dependency to multi-source dependency. However, reports show that about 3,000 public projects face diverse issues related to time and cost overrun. As part of an on-going study to develop a framework for effective public procurement for the Saudi Arabian construction industry, this paper reports the initial findings of the causes of cost overruns in the context of the Gulf State. It also evaluates the interface between some of the front-end loading issues in public procurement in Saudi and their effects on project performance. A systematic review of the existing literature on construction cost overruns, with focus on the Saudi Arabian construction industry has been used. One of the initial findings is that a fixed-price contract is usually used by the client in an attempt to transfer all financial risks to the contractors. This has the unintended consequence of creating a turbulent environment for the delivery of the project which leads to project abandonment by contractors, poor quality of work and substantial rework. Further work is being undertaken to empirically verify the initial findings reported in this paper and their generalizability for the construction industry as a whole.

Keywords: cost overrun, public procurement, Saudi Arabia, construction projects

Procedia PDF Downloads 270

Authors: Nega Tesfie Asfaw, Rafik Absi, Labouda B. A, Ikram El Abbassi

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Composite materials have come to the fore a few decades ago because of their superior insulation performances. Recycling natural fiber composites and natural fiber reinforcement of waste materials are other steps for conserving resources and the environment. This paper reviewed the Thermal properties (Thermal conductivity, Effusivity, and Diffusivity) and Mechanical properties (Compressive strength, Flexural strength, and Tensile strength) of bio-composite materials for thermal insulation in the construction industry. For several years, the development of the building materials industry has placed a special emphasis on bio-source materials. According to recent studies, most natural fibers have good thermal insulating qualities and good mechanical properties. To determine the thermal and mechanical performance of bio-composite materials in construction most research used experimental methods. the results of the study show that these natural fibers have allowed us to optimize energy consumption in a building and state that density, porosity, percentage of fiber, the direction of heat flow orientation of the fiber, and the shape of the specimen are the main elements that limit the thermal performance and also showed that density, porosity, Type of Fiber, Fiber length, orientation and weight percentage loading, Fiber-matrix adhesion, Choice of the polymer matrix, Presence of void are the main elements that limit the mechanical performance of the insulation material. Based on the results of this reviewed paper Moss fibers (0.034W/ (m. K)), Wood Fiber (0.043 W/ (m. K)), Wheat straw (0.046 W/ (m. K), and corn husk fibers (0.046 W/ (m. K) are a most promising solution for energy efficiency for construction industry with interesting insulation properties and with good acceptable mechanical properties. Finally, depending on the best fibers used for insulation applications in the construction sector, the thermal performance rate of various fibers reviewed in this article are analyzed. Due to Typha's high porosity, the results indicated that Typha australis fiber had a better thermal performance rate of 89.03% with clay.

Keywords: bio-based materials, thermal conductivity, compressive strength, thermal performance

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Authors: Yashved Serhun, Kim A. Timm

Abstract:

Barclays Bank has identified the need for a head office building in Lusaka, Zambia, and construction of a 7200 m2 three-storey reinforced concrete office building with a structural steel roof is currently underway. A unique characteristic of the development is that the building footprint is positioned on dolomitic land. Dolomite rock has the tendency to react with and breakdown in the presence of slightly acidic water, including rainwater. This leads to a potential for subsidence and sinkhole formation. Subsidence and the formation of sinkholes beneath a building can be detrimental during both the construction and operational phases. This paper outlines engineering principles which were considered during the structural design of the raft foundation for the Barclays head office building. In addition, this paper includes multidisciplinary considerations and the impact of these on the structural engineering design of the raft foundation. By ensuring that the design of raft foundations on dolomitic land incorporates the requirements of all disciplines and relevant design codes during the design process, the risk associated with subsidence and sinkhole formation can be effectively mitigated during the operational phase of the building.

Keywords: dolomite, dolomitic land, raft foundation, structural engineering design

Procedia PDF Downloads 124