Department of Modeling and Design Engineering Systems

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    EXPERIMENTAL EVALUATION AND CFD STUDY OF THERMAL COMFORT, IAQ INDICES, AND THERMAL ENERGY STORAGE FOR THE IMPROVEMENT OF THE ENERGY PERFORMANCE OF OVERCROWDED AREA
    ( 2022-12-11) AL-MALAKI, Fadhil Asaad Mohammed Kadhim ; JAFARI, Rahim
    In recent years, buildings, including prison halls, have contributed significantly to the world's rising energy use, with 34 % of the energy used by these buildings being attributed to cooling and heating. This study examines the use new combination of phase change materials (PCMs) for energy conservation in buildings through thermal storage, including the use of double layers of PCMs paraffin waxes with different properties. The study evaluates the indoor air quality characteristics of two protocols for cooling and heating in four different scenarios that are classified according to the seasons in a location, with a high daily temperature range, similar to that of Iraq. An experimental facility for the study was designed, constructed, and tested at Technology University in Baghdad. The experimental measurements were taken in a small-scale model 1:4 of a prison quarry, with dimensions of 1.2 by 0.6 by 0.8 meters and a side inlet grill. This prototype model was used to investigate the impact of integrating double layers of panels on the roof of the space and their ability to minimize fluctuations, energy usage, and shift peak load. The computational work involved solving the partial differential equation for the conservation of mass, momentum, and energy and its rate of dissipation using the finite volume technique. Modifications to the algorithm were made to simulate the space with and without PCMs in the roof for all scenarios. The majority of the computed data were presented as temperature contours and other thermal contours, and when compared to the experimental results, a reasonable level of agreement was observed. The use of PCMs as latent heat thermal energy storage (LHTES) in the room envelope for passive cooling has gained significant attention due to their ability to store large amounts of energy. The results of this study show that the use of TES can reduce the energy required for the space by 47.2 % in the summer and in varying proportions during other seasons, also when PCMs are used in hot weather, in door temperature drops by 7 °C at average, compared to when they are not used.
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    LOAD DEMAND FORECASTING USING ARTIFICIAL NEURAL NETWORKS AND FUZZY LOGIC METHODS
    ( 2022-05-12) AL-ANI, BARQ RAAD KHASHEI ; ERKAN, Turan Erman
    This study proposes using artificial neural networks (ANNs) and fuzzy logic (FL) to estimate load demand data to forecast hourly electricity loads in Turkey or 2017 and 2018. We used Real Time Consumption as hourly electric load based on EPİAŞ data for 2017 to 2018. The load forecast was actualized using two machine learning techniques: ANN and fuzzy logic FL. The predicted data was compared to the actual data by plotting on a graph. This study used the ANN and FL methods to optimise the demand for load forecast in Turkey's power systems. The first and last 200 hours were plotted on ANN to get a better visualisation pattern, and the overall estimated hourly load for Turkey was calculated by adding the hourly estimations from each area. The minimum and maximum readings for the year 2017 are 18851.35 MWh and 47062.40 MWh whereas the mean and standard deviation readings are 33102.19 Mwh and 4968.67 MWh. As a result, the comparison of these models was used to forecast the load, all of which have different load patterns and origins. The series are stationary across the year and it peaks during the month of August. The MAPE values for FL for 2017 and 2018 are 3.7986094 and 5.28635983 respectively which is very good and falls in high accurate forecasting results. It can be concluded that the FL gives a better prediction than the ANN for both years. Electrical peak reduction is a vital component of any plan for managing energy demand, and forecasting electric load assists in planning peak load demand reductions to meet energy demand management targets. It can be concluded that the FL gives us a better prediction than the ANN for both years. Home, energy management research will benefit from the new load forecasting models proposed in this study.
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    MODELING SURFACE WATER QUALITY AND NUTRIENT CORRELATION WITH SEDIMENT OXYGEN DEMAND AT DAM WATER RESERVOIR
    ( 2022-09-12) ABDULQADER, Noor N. ; GÜLER, Enver ; NUMANOĞLU, Aslı
    The work presented here is a model approach based on WASP8 (Water analysis simulation program) a water quality model simulated to represent contaminants at the surface and bottom sediments of the Kurtboğazı dam reservoir in Ankara. Investigated water quality output variables were temperature, nitrate, total phosphorus, total Kjeldahl, dissolved oxygen, Chlorophyll a, and ammonium. To ensure that the model represents the actual case at the reservoir, the results from our simulation model were calibrated using actual data from the Kurtboğazı dam site, and the calibration utilizes statistical techniques. The novelty of this research is the development of a quality model to predict the reactions of state variables that are occurring at the water body and how they interact with each other and their influence on the overall quality status of the Kurtboğazı reservoir, as well as the crucial factors influencing the depletion of oxygen at the water column. The accuracy of the model was checked using statistical techniques in the form of coefficient of determination and relative error which produced excellent ranges of results indicating that our simulated model was able to represent the features at the reservoir site. The Kurtboğazı dam reservoir had been affected by the negative impact arising from dissolved oxygen depletion in the hypolimnetic layer during stratification periods. However, the processes of oxygen consumption at the sediment-water interface are still difficult to grasp conceptually and are mainly linked to sediment oxygen depletion and the phenomena of sediment oxygen demand SOD. The work here presents a simulation model that can be utilized as a helpful tool by any person working in the sector of water management, to estimate and predict the parameters influencing the anoxic condition and benthic flux.
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    A BIOINSPIRED CONCEPTUAL DESIGN METHODOLOGY FOR BIOROBOTS
    ( 2013-05-21) KONEZ EROĞLU, Aylin ; ERDEN, Abdülkadir ; ERDEN, Zühal
    The main aim of this thesis is to develop a Bioinspired Conceptual Design (BICD) methodology for design of biorobots. Within the context of the dissertation, a novel BICD procedure has been developed based on existing BID approaches and systematic engineering design steps. This procedure is applied on several case studies, namely a dog biorobot (BioDog) for walking and trotting, a cockroach biorobot (BioCoc) for climbing, a jumping (grasshopper) biorobot for jumping and a hybrid (dog and lobster) biorobot for walking. A BICD process has been developed using the implementation results. Classic DEVS (Discrete Event System Specification) coupled model is used to formally represent the BICD process in order to develop a BICD methodology. The proposed BICD methodology transforms customer needs into a concept design of biorobot with clear and well-defined six design steps. In order to overcome the drawbacks of existing BIDs, the biological system analysis and the bioinspired transformation design steps have been considered in detail. In this thesis, although four case studies have been implemented to demonstrate the BICD methodology, fourteen biological systems and twenty four locomotion types are investigated by using content analysis and/or observation methods. The literature survey has been used for the content analysis method, while an experimental set-up is used to analyze the biological systems for the observation method. Required knowledge on morphology, function and behavior of biological systems are obtained using a high speed camera. During the bioinspired transformation step, the knowledge about the biological system has been transformed systematically into knowledge about the biorobots and this knowledge is used to develop the concept design of biorobots.
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    DEVELOPING NEW EVALUATION METRICS TO MEASURE AND IMPROVE SUPPLY CHAIN PERFORMANCE AND FLEXIBILITY WITH SUCCESSFUL ERP IMPLEMENTATION AND BPR APPLICATION: A HYBRID FUZZY AHP / ANP / STATISTICAL ANALYSES APPROACH
    ( 2013-06-21) BAÇ, Uğur ; ERKAN, Turan Erman
    Supply Chain Management and flexibility has gained a great importance nowadays. Consideration of performance and flexibility of supply chains are popular research topics. To maintain competitive advantage on the market, continuous benchmarking and improvement in performance is mandatory. To adapt continuously changing market conditions, supply chain structure should be flexible. Successful ERP implementation has a considerable effect on supply chain flexibility when it is supported by a BPR application. Some special metrics are needed to evaluate overall supply chain performance and flexibility to achieve and track improvements. In this study, two new evaluation metrics have been developed to evaluate performance and flexibility by a hybrid approach with MCDM models and statistical analyses. Also prerequisites needed for a successful ERP implementation and BPR application have been specified. As a result of this study, a road map has been prepared for benchmarking and improving Supply Chain performance and flexibility by successfully implementing ERP and applying BPR.