The Improvement of the Evaluation and Classification in Degree Disability Assessment

Disabled persons represents a cathegory of the social assistance’s beneficiaries who needs furher contribution on behalf of the society, moreover the granted support currently offered by the caregivers for the purpouse of faceing the daily social needs and for a decent existence. The special situation of the disabled persons from the viewpoint of functionality, the existent concerning rate of the abuses within the system, but also the increased number of system’s beneficiaries, both underprivileged and privileged to fraud limit and over it, established the premises with the view of accomplishing this study. The research consisted in analyzing the specific national and international legal framework, of the existent data within the central public administration, which represent the coordination activity of the specific system, as well as of the collected national data. The present study is intended to emphasize the system’s organizationally and functionally deficiency, whereas to externalize the proposals and develop it into improved solutions for the quality life of the disabled persons.disabled persons, evaluation sistem, classification system in degree of disability, evaluation system tools, social assistance, social inclusion.

Identifying Optimal Design of Office Buildings Using Harmony Search Optimization Algorithm

Energy is an expensive and scare resource and the world faces an energy crisis given our dependence on the limited supply of fossil fuels. Similar to other countries, in Qatar, energy consumption and the subsequent production of greenhouse gas emissions are becoming a major challenge that the society is facing. Recent statistics in Qatar indicated that the per-capita use of electricity and production of CO2-emission has been rising continually since 1971. Population growth and industrial development are the main sources of these problems. In 2004, the electricity consumption per capita reached 17000 kWh which puts Qatar as one of the highest energy consumer per capita in the world as it surpasses the average per-capita electricity consumption of the developed countries. Due to the high contribution of buildings in overall energy consumption, building energy performance has become a key approach to reduce energy consumption and the associated greenhouse gas emissions. Since the building energy performance depends on the numerous variables related to the building characteristics, installed equipment, occupants' behavior, and environmental loadings, selecting the most efficient combination of variables is highly complicated. Considering other objectives such as reduction of financial costs and minimizing the life cycle emission will increase the complexity of the decision making process. To solve these problems, different numerical methods such as optimization algorithms are proposed and utilized. Multi-objective design optimization is a powerful tool to assist decision makers identify and implement the most efficient strategies. The multi objective optimization algorithms are capable of determining the proper variables to obtain the optimum design. Therefore, the objective of this work is to tackle the problem of determining the best design by implementing a harmony search (HS) based optimization algorithm to minimize the life cycle cost and life cycle CO2 equivalent emissions of a small office building. Parameters considered in the current investigation model are building materials and their associated thickness in different building components including wall, floor, roof, and ceiling. In addition, different HVAC systems are considered as design variables. HS algorithm was conceptualized using the musical process to identify the perfect state of harmony. HS was initially developed for the discrete variable optimization problems and then expanded to include continuous variable problems as well. Simplicity in implementation and flexibility of the algorithm has increased the utilization of this method in many research fields. In difference with other optimization methods which are usually based on the numerical linear and nonlinear programing methods that require gradient information to seek the solution, HS algorithm does not utilize gradient information. To achieve this objective, price data and emission data are collected and magnitudes of each one calculated according to the simulation results. The first objective is to minimize the life cycle cost of the design. To identify the life cycle cost of each model, the summation of present value of initial costs, operation and maintenance costs, and energy costs are calculated. The data for construction costs are taken from construction handbooks. In this study, the building life is assumed to be 40 years. For the life cycle assessment, all phases of pre-use (extraction, transfer, and processing of materials), use (service and maintenance), and end-of-life (demolishing and transfer of wastes) of the modeled building have been considered. The pre-use phase costs include the material prices, labor costs, replacement, and equipment. The use-phase includes the service energy costs (heating, cooling, water heating, lighting, equipment, etc.) which are determined by the energy simulation. The second objective of this study is to minimize the life cycle emission of the design. The life cycle emission of each design is determined based on the emission of global warming potential (GWP) data of different materials during pre-use, use, and end-of-life. The pre-use emission can be calculated by having the weight of each material used in construction of the building and multiplying with the emission amount per unit weight. The environmental emission data are collected through different LCA datasets such as DEAM and EcoPack. The use phase emission includes two types of emissions: energy related and service-maintenance. For the energy related emissions, the emission factor of electricity consumption is determined according to the location and source of energy generator systems. To calculate the maintenance emission during the use period, a list of materials and mass of each which should be replaced was prepared. The post-use phase energy consumption includes all the emissions related to demolition and disposal of wastes and the regarding data were gathered through life cycle analysis data bases. In order to optimize the process of designing of the small office building in this study, a C++ code which is capable of modifying model characteristics, perform energy simulation, evaluate the results, and identify the next simulation magnitudes was developed. The proposed HS optimization algorithm, first selects and assigns random magnitudes for the initial values of variables. This selection is a random selection through the defined ranges for variables. Then a simulation of the initial model is performed to attain the first sets of results (objective functions). HS algorithm evaluates the objectives and sets the new values for variables for next simulation. The results of next simulations will be compared with results of previous simulations. If the results in each simulation are better than worst solution, worst solution will be replaced by new results. The solution of the optimization problem improves by having multiple simulations gradually. To determine the energy consumption of the building in the use phase, EnergyPlus model of the building including building envelope system details, thermal zones temperature set points, occupants' activity type and schedule, types of HVAC system, equipment loadings, lighting system schedule, and design year weather data was prepared. EnergyPlus is a powerful energy simulation program for modeling building energy performance and capable of modeling multi-zone airflow, thermal comfort and natural ventilation systems, as well as determining the amount of energy was utilized to determine the total building energy consumption. The focus of this study is to determine the optimum building construction materials and their associated thickness as well as HVAC system of a small office building located in Doha, Qatar. Heat pump air to air ventilation system is assigned to this building and zones' temperature set points are fixed on 22 °C for heating and 26 °C for cooling. Running the simulation process parallel to the optimization algorithm evaluation resulted in identifying multiple optimum solutions of building construction materials and their associated thickness as well as HVAC system. In order to offer decision makers the chance to evaluate the tradeoff between cost and emissions, the Pareto front is plotted. In addition, comparing designs with different life cycle costs and emissions resulted in the following conclusions: By comparing the life cycle cost and carbon dioxide emission of different designs, it was concluded that assigning a small modification in life cycle cost can significantly change the CO2 equivalent emissions. Foundations, floors, and ceilings are emitting the highest amounts of carbon dioxide equivalent in building. Using of high emission materials with higher thickness comparing to other construction materials are the main reasons of this contribution. The outcomes of this research, assists designers in identifying the best combination of envelope materials to design energy efficient buildings. It remains for future to investigate the effects of working schedule, and control strategies in optimum design of buildings.qscienc

Seasonal variations in nutritional profile of the freshwater mud eel, Monopterus cuchia (Hamilton, 1822)

Seasonal variations of proximate compositions, amino acids, and fatty acids contents of Monopterus cuchia were studied for the first time in Bangladesh. The fat and fatty acid, protein and amino acid contents showed a significant seasonal dependency. Lipid contents showed the wider variation than the protein contents. Among the 14 recorded amino acids, the primary amino acids were lysine, glutamic acid, arginine, glycine and aspartic acid. The ratio of essential and non-essential amino acids was higher in the post-monsoon season (0.69) than pre-monsoon (0.68) and monsoon season (0.68) and did not show seasonal discrepancies. The amount of fatty acids were found in order of saturated fatty acids (SFA) > mono unsaturated fatty acids (MUFA) > polyunsaturated fatty acids (PUFA). The predominant fatty acids were palmitic and stearic acids of SFAs, oleic and palmitoleic acid of MUFAs and linoleic and α linolenic acids of PUFAs group. The combined value of EPA+DHA varied from 1.44–5.34% depending on the season, with the highest in monsoon season. However, the n-6/n-3 ratios were notably lower (0.58–2.51) throughout the season than the greatest esteem of 4. Therefore, M. cuchia may be consumed as healthy as safe food with reference to n-6/n-3 ratio, irrespective of catching seasons

Impregnation and encapsulation of lightweight aggregates for self-healing concrete

This study investigated a technique of impregnating potential self-healing agents into lightweight aggregates (LWA) and the self-healing performance of concrete mixed with the impregnated LWA. Lightweight aggregates with a diameter range of 4–8 mm were impregnated with a sodium silicate solution as a potential self-healing agent. Concrete specimens containing the impregnated LWA and control specimens were pre-cracked up to 300 μm crack width at 7 days. Flexural strength recovery and reduction in water sorptivity were examined. After 28 days healing in water, the specimens containing the impregnated LWA showed ∼80% recovery of the pre-cracking strength, which accounts more than five times of the control specimens’ recovery. The capillary water absorption was also significantly improved; the specimens healed with the impregnated LWA showed a 50% reduction in the sorptivity index compared with the control cracked specimens and a very similar response to the control uncracked specimens. The contribution of sodium silicate in producing more calcium silicate hydrate gel was confirmed by characterisation the healing products using X-ray diffraction, Fourier transform spectroscopy, and scanning electron microscopy.Yousef Jameel Foundation through Cambridge Commonwealth, European & International Trust, Engineering and Physical Sciences Research Council (Project Ref. EP/K026631/1 – ‘‘Materials for Life”

The use of oil-based mud cuttings as an alternative raw material to produce high sulfate-resistant oil well cement

Oil-based mud (OBM) is used during the oil well drilling processes to cool drilling pits and remove the cuttings. As a result of these processes, the oil-based mud (OBM) cuttings are produced. The composition of the OBM cuttings depends on the geological conditions of the boreholes and the OBM used during the drilling operation. In this study, the OBM cuttings were used as an alternative material to produce a special cement known as oil-well cement (OWC). Raw meal mixtures were prepared with various percentages of OBM cuttings (5, 11, 13, 15, 18, and 20%). Then they were sintered up to a temperature of 1450 °C, and the resulting cement clinker was ground to produce highly sulfate resistant OWC. The burnability of the raw meal was studied to explore the effect of OBM cuttings on raw meal behavior during the clinkerization process. The results of the study indicated a decrease in the decarbonation temperature and an increase in the rate of clinkerization as the OBM cuttings increased. The produced cement was tested per American Petroleum Institute’s testing procedure for OWC. Also, the cement hydration for 2, 7 and 28 days was carried out to study the behavior of the produced OWC

The Enhancement of Nonlinear Ultrasonic Testing to Detect Micro-structural Defects in Metals

Second harmonic generation (SHG) is a nonlinear ultrasonic testing (NLUT) method, which is based on the distortion of a single frequency wave confronting the micro-structural features as it passes through the material. This distortion generates higher frequency components of the fundamental frequency. The amplitudes of the fundamental and second harmonics are used to calculate the acoustic non-linearity parameter (β). The acoustic non-linearity parameter is correlated with the extent of micro-structural features in materials; however, the major challenges of this method are high sensitivity of harmonic amplitudes to the signal processing method and the experimental variables, such as coupling condition and instrumental non-linearities, which introduce significant variability in the reported non-linearity parameters representing different defects. The objective of this research is to minimize the variability of non-linearity parameter in relation to damage by introducing wavelet-based signal decomposition approach, and blocking the non-linearity in medium and instruments by phononic crystals (PCs). The research has two major components: (i) understanding the major drawback of the most prevalent signal processing method and formulating a more robust harmonic decomposition method, and evaluating the proposed method in the NLUT experiments to detect plastic strain and creep damage; (ii) blocking the non-linearity generated in instrument and couplant (water for the case of immersed NLUT) by implementing one-dimensional PCs, known as superlattices (SLs). It is demonstrated that the wavelet-based signal decomposition reduces the variability of harmonic amplitudes as compared to Fourier transform-based signal decomposition. SLs are numerically modeled to block higher harmonics selected in this research, and evaluated experimentally. It is shown that non-linearity in water and electronics in the transmission side of data acquisition equipment can be blocked while the NLUT method can be used with immersion method with the reduced coupling effect. The NLUT method integrated with SLs is demonstrated on detecting plastic deformation in aluminum and creep damage in steel

Framework for Energy-Efficient Building Envelope Design Optimization Tool

© 2018 American Society of Civil Engineers. Multiple energy-simulation programs have recently been developed. Most of these programs utilize thermodynamic equations and the mechanical characteristics, loadings, and temperature set points of the building to predict the total energy demand in a year. In addition, numerous building design parameters, including building envelope, window-to-wall ratio, and building orientation and shape, influence the level of energy consumption, which makes the design process complicated. Challenges that manifest within these systems are inherently complex and interdisciplinary in nature, and they often defy linear, cause-and-effect correlation, which makes the simulation of building energy performance even more complicated. In addition to the difficulty of determining the best design parameters, multiple numbers of objectives, such as the life-cycle cost and environmental emission of the project, increase the complexity of the problem. Therefore, a proper multiobjective optimization algorithm tool that is capable of eliminating a portion of trial-and-error process is needed. This article presents a framework for developing a multiobjective design optimization tool that is capable of identifying the designs with the lowest life-cycle cost, lowest life-cycle emission, and highest occupant thermal satisfaction. To demonstrate the application of this framework, the development of the design optimization tool using a C# program is presented. The building envelope, as the major barrier between the outdoor environment and inside conditioned zone, was considered as the main building component to optimize. To calculate the occupants' thermal satisfaction, a predicted mean vote method (PMV) was used. Even though the theoretical basis behind this tool is robust and accurate, the developed tool is simple, flexible, and user-friendly to encourage its use among designers and engineers. It is expected that the developed tool will ease the integration of energy efficiency in commercial buildings.The authors acknowledge the financial support for this study through a grant from the Qatar National Research Foundation (QNRF)/National Priorities Research Program (NPRP)

Development of an Integrated Quality Function Deployment and Utility Theory Weighting System to Improve Occupants' Satisfaction

Studies have shown that occupant satisfaction is a compelling factor affecting building energy consumption. Occupants' behavior has a direct relationship to their satisfaction, and it is clear that occupants' satisfaction is highly impacted by the indoor environmental quality. To identify the best design, parameters influencing occupants' perception as well as other competing objectives should be contemplated. In recent years, various multiobjective optimization algorithms have been developed to determine the best design strategies. However, occupants' satisfaction and the effect of different strategies on it comprise the missing component of these studies. Therefore, this study aims to identify the parameters influencing occupant satisfaction and develop a weighting system that can reflect these requirements in addition to the constructors' perception. To attain this objective, a survey study was conducted to identify the parameters affecting end users' satisfaction. To evaluate the construction experts' perspective regarding the identified parameters, an experts' utility function was calculated for the determined parameters. Furthermore, using the single-attribute utility and multiattribute utility, a weighting system was developed and assigned to each satisfactory requirement.Qatar National Research FundScopu

IFC-Based BIM-to-BEM Model Transformation

Building information modeling (BIM) can facilitate evaluation of the energy performance of a building from the early stages of a project. However, due to differences in how information is represented in BIM and building energy modeling (BEM), the exchange of data between the two tools is tedious and error prone. This paper presents research on leveraging open BIM standards for facilitating energy analysis BIM use. An extension was developed for OpenStudio that transforms building information models represented in Industry Foundation Classes (IFC) files into building energy analysis models in the OpenStudio data format. In the defined workflow, the model transformation is performed by a serializer that was developed using the open source BIMserver, while the OpenStudio extension transitions models between OpenStudio and BIMserver. The model transformation algorithm and its implementation in BIMserver were validated in a case study by comparing the actual energy demands of a building with the predicted energy demands of a simulation model that was created through the developed workflow