Knowledge University is a private university that was established in 2009. The university is licensed by the Ministry of Higher Education & Scientific Research in the Kurdistan Region of Iraq. The university can accommodate up to 4000 students and this figure is the minimum estimation based on the current spaces available. At the time of writing this there are more than 2600 students enrolled in the university. The university’s campus is located in the suburbs of the city of Erbil, near Kirkuk road.The campus spans about 1,125 Square Km of land, encompassing modern-style architecture buildings and huge car parking lots surrounded by beautiful gardens. The campus is one of the best campuses in the country known for its green and sustainable program objectives.In addition, the university has many other facilities such as an external conference hall and an auditorium hall each spanning 2275 Square meters. Other facilities include a football field, basketball court, cafeterias, and a restaurant. Access to all buildings is facilitated either by walkways throughout the many gardens within the campus.There are numerous labs within the different faculties. These labs are equipped with all the necessary equipment and instruments required for conducting relevant experiments and tests. There are several computer labs with internet/intranet access.The university campus has the potential for future expansion and there are plans for new colleges and departments.
The change toward sustainable energy arrangements necessitates state-of-the-art approaches for simultaneous waste valorization, clean hydrogen production, and resource recovery. Accordingly, this study proposes an integrated anaerobic digestion-based biomass-to-liquefied hydrogen system incorporating a proton-conducting solid oxide fuel cell (HSOFC), humidification–dehumidification (HDH) desalination, proton exchange membrane electrolyzer (PEME), and Claude liquefaction cycle. In the proposed configuration, anaerobic digestion converts the biodegradable fraction of municipal solid waste to biogas, which is utilized as the fuel for HSOFC to generate power and recoverable heat-based energy. The HSOFC exhaust heat is recovered to supply the thermal requirements of the anaerobic digester, HDH desalination unit, and PEME, while a portion of the electricity generated drives hydrogen production for subsequent liquefaction and storage. Following model validation, the system is comprehensively assessed from a 4E perspective, encompassing energy, exergy, economic (exergoeconomic and net present value), and environmental (life-cycle assessment, exergoenvironmental, and CO2 emission) analyses. Parametric and sensitivity analyses are performed, followed by artificial neural network (ANN)-based machine learning modeling and triple-objective optimization using the pareto envelope-based selection algorithm-II (PESA-II) coupled with TOPSIS. The objectives are the output liquefied hydrogen rate (LH2R), unit cost of products (UCOP), and specific exergoenvironmental impact (SEI). The optimal solution achieves a LH2R of 822.1 kg/day, a UCOP of 24.88 $/GJ, and a SEI of 8.41 mPts/GJ, with 5522.4 kW total exergy destruction rate, 148.88 $/h investment cost rate, and 77.63 mPts/h environmental impact rate. Findings reveal the feasibility of combining anaerobic digestion with HSOFC-based multigeneration and hydrogen liquefaction for sustainable waste-to-energy conversion.
This article inspects the bioconvection flow of second-grade nanomaterial in a magnetic field upon a revolving stretching disk under the Darcy-Forchheimer theory. Radiated heat, heat generation/absorption and chemical reaction have been incorporated. Thermal and solutal convective conditions are assumed to compute heat and mass. The Buongiorno nanofluidic is assumed to simulate Brownian movement and the force of thermophoretic. Considering a porous substance, a Darcy-Forchheimer theory is implemented, and to simulate non-Newtonian characteristics such as the second-grade model is applied. The complex dimensionality PDE's in terms of microorganism, energy, momentum and energy are renovated into an ODE by employing suitable similarity variables. The renovating ODEs are tackled through NDsolve technique, and the influence of the newly discovered variable on the microorganism, temperature, concentration and velocity mechanisms has been displayed graphically and in tabular form. It is being suggested that despite growing the magnetic variable, the inertia coefficient and the fluid variable lessen the radial and azimuthal velocity field. The porosity effect and stretching parameter intensify the axial velocity. Additionally, the temperature and concentration augment in tandem with the enhancement of thermal and solutal Biot number. The results of this research seem substantially applicable to spinning biological nanotechnologies production structures, permeable disk devices, thermal energy gadgets, including medical transportation systems wherever accurate oversight of thermal energy, weight, and biological nanofluid transportation is required. The current findings offer valuable scientific insights and highly design advice toward sophisticated rotary disk mechanisms working in permeable, highly conductive conditions.
Coffee is one of the most widely consumed beverages worldwide, and its high economic value makes it vulnerable to adulteration with low-cost materials. Detecting such fraud is particularly challenging when adulterants are present at low levels and do not cause obvious sensory changes. In this study, an electronic nose (e-nose) system combined with multivariate analysis and machine learning was evaluated for the detection of common adulterants in medium-dark roasted Arabica coffee. Coffee samples were adulterated with soybean, wheat, and barley flour at five weight percentages (10–50
Among the various ideas in graph theory, labelling of graphs has diverse applications in cryptography, coding theory, data security, telecommunication networks, etc. Labeling of a graph is any mapping that, under specific circumstances, converts a given collection of graph components to a given set of numbers. In this paper, we determine the exact value of reflexive edge irregularity strength of the barycentric subdivision of circulant graphs C_p[1,k_1] .
The growing need for sustainable energy solutions in modern power systems emphasizes the importance of optimizing microgrids to address the critical challenge of effectively managing and integrating local renewable resources, energy storage systems, and electric vehicle charging stations. For this reason, this paper investigates the optimal sizing and energy management of a hybrid grid-connected microgrid incorporating local AC loads, renewable energy units, energy storage systems, and DC loads in the form of an electric vehicle charge station. A comprehensive optimization framework is developed to effectively balance energy supply and demand in order to have minimized levelized cost of energy (LCOE) and life cycle environmental emissions (LCEE). This study also incorporates the annual growth rate of local energy demand into the optimization framework. It is considered to make sure that the size of renewable units and the energy storage system, and also their energy management, will be adaptive to future demand fluctuations. The numerical evaluation of the proposed method demonstrates its effectiveness in optimizing the sustainable microgrid with a low LCOE and a reduced LCEE. The optimized configuration demonstrates superior operational efficiency.
