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In this study, a new water and power cogeneration plant, employing photovoltaic (PV) and photovoltaic–thermal (PVT) panels simultaneously, is designed and optimized for a village struggling to provide energy and potable water in Iran. The system includes a solar energy unit to generate clean electricity and heat, and a reverse osmosis unit to produce drinking water. Techno-economic optimization is performed by implementing a genetic algorithm, and a comprehensive water and energy management strategy is designed and presented in detail, expandable for future works. A new method, the logarithmic model, is used to calculate the depth of discharge (DOD) of lithium-ion batteries, which was previously a fixed and predetermined value in previous papers. Various indices, the constraints of the optimization process, are also introduced to measure the reliabilities of different units. The effects of the system components on total cost are investigated and a comprehensive sensitivity analysis is performed to find the best solution to increase the penetration of renewable-energy systems. The results reveal that considering the depth of discharge of batteries and water storage tank capacity as decision variables reduces the system’s life-cycle cost (by 5.1% for changeable DODs). Furthermore, the simultaneous use of PV and PVT panels decreases the life-cycle cost considerably by ≤19% compared with the use of only PVT panels. Additionally, the cost of the battery causes a decrease in the cost of electricity storage and the cost of producing and storing fresh water.

Electricity plays a vital role in the economic development and welfare of countries. Examining the electricity situation and defining scenarios for developing power plant infrastructure will help countries avoid misguided policies that incur high costs and reduce people’s welfare. In the present research, three scenarios from 2021–2040 have been defined for Iran’s electricity status. The first scenario continues the current trend and forecasts population, electricity consumption, and carbon dioxide emissions from power plants with ARIMA and single and triple exponential smoothing time series algorithms. As part of the second scenario, only non-hydro renewable resources will be used to increase the electricity supply. By ensuring the existence of potential, annual growth patterns have been defined, taking into account the renewable electricity generation achieved by successful nations. The third scenario involves integrating operating gas turbines into combined cycles in exchange for buyback contracts. Economically, this scenario calculates return on investment through an arrangement of various contracts for the seller company and fuel savings for the buyer.

In common parabolic trough solar collectors (PTC), solar irradiation is concentrated at the bottom of the absorber tube, causing high surface temperatures, thermal stresses, and deflections with subsequent damages and costs. Also, the performance improvement of PTCs is always of significant importance. The new idea of rotating the absorber tube is proposed, and its effects on the PTC performance are studied experimentally. The effects of the working fluid flow rate (Re number) and the rotational velocity of the absorber tube (Ta number) on the energy characteristics of the PTC are analyzed. Results indicate that the optimal selection of the rotational speed makes it possible to reduce and control the temperature of the absorber by about 60% reduction in the fluid-tube temperature difference, and 15% reduction in the maximum surface temperature. Furthermore, about 17% enhancement in the efficiency of the PTC is attained. The share of the natural and both the rotational and mass flow forced convection forces in the total heat transfer is analyzed through Gr, Re, Ta, and a convection evaluation parameter (CEP). Ta/Re ratio and CEP provide valuable information such that, CEP T a / R e ≈ 0.5 led to the highest efficiency (average and maximum efficiencies of 30% and 87% respectively).

Owing to its severe hydrophobicity, graphene (G) as on dispersed in a fluid usually deposits therein after a short interval of time. Understanding the G-behavior and the factors affecting its deposition could pave a way for creating a substantially stable nanofluid (NF). In this work, a novel method of stabilizing a G-NF is described with selective examples. The results can be extended to develop the science and technology of G-NFs in general. Electrohydrodynamic forces are used as a controlling factor in the presence of magnetic nanoparticles (MNPs). Contrary to common chemical methods employed for preparing G-NFs, which depend on establishing bonds between the components, the physical method introduced in this article could be used as a novel approach not only to dispersing G in a fluid carrier but also to resolve the common problems originating from utilizing such chemical methods as increasing thermal resistance through adding various types of surfactants. The effects of various factors on the stability of the G-NFs are described. By increasing 50%, 100% and 170% of G, the G sitting rate increased by 43%, 82%, and 109%, respectively. With the addition of one, two and three layers to a G-monolayer, the G sitting rate grew by 77%, 153%, and 263%, respectively. Further, the G-behavior in the presence of MNPs and varied intensive electric fields were studied to optimize an electric field that could stabilize a single-layer G sheet in aqueous NFs. Adding MNPs promptly stabilizes a water/ethylene glycol/G NF in an applied electric field of 0.05 V/Å.

Phase change materials (PCM) have had a significant role as thermal energy transfer fluids and nanofluids and as media for thermal energy storage. Molecular dynamics (MD) simulations, can play a significant role in addressing several thermo-physical problems of PCMs at the atomic scale by providing profound insights and new information. In this paper, the reviewed research is classified into five groups: pure PCM, mixed PCM, PCM containing nanofillers, nano encapsulated PCM, and PCM in nanoporous media. A summary of the equilibrium and non-equilibrium MD simulations of PCMs and their results is presented as well. The primary results of the simulated systems are demonstrated to be efficient in manufacturing phase change materials with better thermal energy storage features. The goals of these studies are to achieve higher thermal conductivity, higher thermal capacity, and lower density change, determine the melting point, and understand the molecular behaviors of PCM composites. A molecular dynamics-based grouping (PCM simulation table) was presented that is very useful for the future roadmap of PCM simulation. In the end, the PCFF force field is presented in detail and a case problem is studied for more clarity. The results show that simulating the PCMs with a similar strategy could be performed systematically. Results of investigations of thermal conductivity enhancement showed that this characteristic can be increased at the nano-scale by the orientation of PCM molecules.

Energy distribution companies use various vehicles such as Outage Elimination Maintenance Vehicles (OEMVs), Maintenance Vehicles (MVs) and Supervision Vehicles (SVs) in order to resolve network faults, to conduct inspection, service and maintenance activities and to monitor the integrity of operations. These vehicles have different levels of fuel consumption which concerns companies with regards to the cost and environmental hazards. Hence, it is important to know that a distribution company how many and what types of vehicles do need to predict the fuel consumption of these vehicles. Extra fuel consumption may be required owing to carry unnecessary equipment or used vehicles with large engine volume. Therefore, in this paper, the fuel consumption levels of outage elimination maintenance, maintenance, and supervision vehicles are considered. Then, given the fact that fuel consumption increases with the increase of vehicle weight and Engine Displacement (ED), the extra fuel consumption has been predicted using Artificial Neural Networks (ANNs). In a case study, the total annual fuel cost in the network under consideration is estimated to be $66750. In the case of a 40% increase in vehicle weight, the fuel consumption cost will rise by $24500, and when the engine displacement increases for a 500 CC, the cost rises up $17400 per year.

In this research work, hierarchical porous carbon foams (CFs) with high surface area and three dimensionally (3D) interconnected macro/meso/microporous structures were prepared through pyrolysis of stabilized poly(acrylonitrile-co-divinylbenzene) P(AN-co-DVB) polyHIPE foams at 900 °C under nitrogen atmosphere. The prepared CFs revealed high surface area (540 m2 g−1), semi-ordered nanoporosity, high electrical conductivity (470 S m−1) and high graphitization degree. Further, HR-TEM observation of CFs revealed the formation of graphitic domains in the structures. The obtained CFs were employed for encapsulation of phase change materials (PCMs) e.g. paraffin (PA) and polyethylene glycol (PEG). The prepared PCMs composites revealed the excellent reversible thermal/chemical stability after frequent 200 heating/cooling cycles. Black CF/PA and CF/PEG composites can be promising structures to be driven either by applying a small voltage (3–3.6 V) with high electric-to thermal efficiency (up to 85%) or by irradiating with sunlight with high photo-to thermal efficiency (up to around 91%).

In this investigation, a polygeneration scheme integrating local desalination units with CCHP systems, providing cold, heat and power for Kish twin towers as well as providing a portion of the fresh water demand of the island, is proposed and evaluated in terms of energy, environment, and economy aspects. The proposed system is compared to the conventional CCHP and desalination system adopting the separate production system as the reference. Here, two types of desalination technologies, namely multi-effect distillation (MED) and reverse osmosis (RO) processes, are used to provide desalinated water. A genetic algorithm is implemented to determine the optimal operating parameters. It results in that in the polygeneration system the yearly average power generation efficiency, the annual primary energy saving ratio (APESR) and the annual total cost saving ratio (ATCSR) of the whole system increase by 3.45%, 9.73%, and 6.49%, respectively, compared to the conventional system. Using the MED process can increase the ATCSR from 9.8% to 16.0%, depending on the fresh water market price. Moreover, the carbon dioxide emission (CDE) decreases by 1460.5 tons each year, compared to the reference. It is also indicated that 93.87% of the MED input heat can be recovered for domestic hot water (DHW) provision.

In this research work, a three dimensionally (3D) interconnected porous polystyrene-carbon nanotubes (PS-CNT) polyHIPE foam was developed as a phase change material (PCM) scaffold for photo-to-thermal energy storage applications. Structural and thermal properties of the novel phase change composite were characterized by scanning electron microscopy (SEM), Fourier transform infrared (FT-IR) spectroscopy, X–ray diffraction (XRD) spectroscopy, ultraviolet-visible diffused reflectance spectroscopy, differential scanning calorimetry (DSC) analysis, and laser flash analysis. The paraffin/PS-CNT composite containing 1 wt% CNTs exhibited a thermal conductivity as high as 0.39 Wm-1 K-1, 1.62 fold higher than that of pure paraffin. The highly porous structure of the prepared foam led to a high PCM loading of 82.5%, a high latent heat of 119.3 J g-1 and a melting point of 56.88 °C. The prepared composite preserved its stable thermophysical properties after 100 melting/solidification cycles. The enthalpy of paraffin increased about 3.5% after infiltrating into the PS-CNT polyHIPE foam. Further, the composite displayed excellent shape stability, which prevented the leakage of phase change material during phase transitions. Incorporation of carbon nanotubes in the polyHIPE foam led to black color of the composite leading to an increase in the light absorbance efficiency and especially the light-to-thermal energy conversion efficiency (90%).

The increasing consumption of energy and the numerous obstacles in the way of its extraction, including diminishing fossil fuels and the turn towards renewable energies, environmental changes, a tendency towards systems of information networks, rising costs of energy and advancement of technology have made the need for new technologies aimed at efficient management of energy more imminent. The Internet of Energy (IoE) technology has been recognized as a novel and efficient strategy that provides the necessary tools for optimal energy management. The present study was carried out with the purpose of identifying key components in implementation of IoE in Iran. This study is practical in its goal and descriptive-explorative in its methodology. First, the data were categorized using the qualitative method of meta-synthesis and using the Sandelowski and Barroso method. The statistical population of the study was the scholarly finding of 2010–2021 and 55 papers were sampled from the published works. The kappa coefficient was used to determine reliability and quality control. The kappa coefficient calculated with SPSS equals 0.87, which falls in the “excellent” category. Second, the frequency and importance of each component was determined using the Shannon entropy technique. The purpose of this method is to measure the weight or importance of each component based on frequency and to identify the key components. Third, the MICMAC structural analysis method was used to evaluate the influence/dependence of components by eight experts in the field of energy and determine strategic components. The purpose of this step is to compare the results with the results of the second step of the research. The results show that 82 indicators play a role in implementation of the concept of IoE; these indicators can be divided into ten axial categories of rules and regulations, individual and human factors, funding, technological infrastructure, cultural and social factors, security factors, technological factors, knowledge factors, learning style, and management factors. In the Shannon entropy method, technological infrastructure, management factors, and rules and regulations are the most significant, respectively. In MICMAC structural analysis, the components of managerial factors, technological infrastructure, and financing have the largest share in influence and dependence, respectively. Conclusion: The two components of management factors and technological infrastructure can be considered as key and strategic components in implementation of IoE in Iran.

Antibacterial low-melting-point poly(ethylene terephthalate) (LMP-PET) fibers are produced via melt spinning. First, LMP-PET granules are modified by free radical graft polymerization of acrylamide (AAm), an N-halamine precursor, using a twin-screw extruder to conduct reactive melt extrusion. The modified granules are spun into fibers using a melt spinning machine. The fibers are characterized by various analytical techniques. Potent rechargeable antibacterial properties of the fibers are assessed and demonstrated by zone of inhibition test, counting bacterial colonies, and imaging of dead bacteria. It is shown that increasing AAm concentration yields to enhanced rechargeable antibacterial properties while fibers structural properties are preserved.

This investigation is devoted to the optimizing a novel pressurizable liquid piston Stirling engine (PLPSE) using particle swarm optimization (PSO) algorithm. The influences of design parameters including pressure intensifier coefficient, pressure intensifier mass, spring stiffness of the intensifier part of the system, the height of the hot and cold liquid columns and the power piston cross-sectional area on the hydraulic output power of the proposed system are studied. Through sensitivity analysis, it is found that some of the parameters have significant effects on the performance of the proposed PLPSE. Based on maximizing the hydraulic output power and stability of the system's steady-state dynamic behavior, some normalized objective functions are defined, and they are converted into a single objective function via weighting summation method. Then, the optimal values of the decision variables are found via an optimization scheme using PSO algorithm with the purpose of minimizing the objective function. Next, the success of the proposed design approach is examined through simulation results. Finally, the designed PFPSE is fabricated and principally tested. It is shown that the mathematical model based results are in a good accordance with the experimental results through which validity and reliability of the presented design method are attained.

Implementation of the Cold Thermal Energy Storage (CTES) system is one of the effective ways to reduce energy consumption and damping environmental pollutions. In this study, a household refrigerator with ceiling type evaporator is considered to equip it with CTES system. According to ASHRAE standard, the temperature ranges of the household refrigerator is between 274 and 280 K, and hence water is used as phase change material (PCM). Owing to the low thermal conductivity of water impact of the extended surface in the container was investigated. Hence, first, a bare cubic PCM container, as well as several finned containers, are examined, numerically. Bare PCM container could maintain the refrigerator’s cabin temperature in the standard condition, just for 30 min. Results show that adding three fins to PCM container, as the best choice, can keep the refrigerator’s temperature in the standard temperature range for 68 min. In consequence, the operation of the refrigerator equipped with a PCM container with three fins is examined, experimentally. The experimental results of charging and discharging process show the good consistency with the numerical results. Furthermore, it is obtained that using finned CTES system, would reduce compressor’s energy consumption about 17.4% per day. Due to lower electrical demand for refrigerator, it would diminish the fossil fuel consumption and carbon dioxide emission for 12 L and 28 kg, respectively.

This paper describes the comprehensive mathematical modeling, simulation and finally validation the developed dynamic equations of a pressurizable liquid piston Stirling engine. The proposed system comprises of the main following components: solar fresnel lens, hot, cold and tuning liquid columns, regenerator, solid pressure intensifier, liquid power piston and output water column. The mathematical modeling of the proposed system is divided into distinct parts, including dynamic of working gas pressure, hot, cold and tuning liquid columns and dynamic of the output part of the system. The obtained dynamic differential equations are rewritten to nine first order differential equations and solved employing 4th order Runge-Kutta numerical method. The pumping head of 1.5 m, the hot and cold side temperature of 100 °C and 20 °C, respectively and zero dead volumes are considered. It is obtained that the working gas pressure has the oscillatory behavior between two upper and lower points, frequently. According to the oscillatory dynamic of working gas pressure, when the working gas pressure is high enough, it can push the liquid power piston to overcome the static pressure of the output column of the pump and finally the water pumping occurs.

In general, one of the promising methods to reduce energy consumption and off peak load is the employment of cold thermal energy storage (CTES) in energy systems. In this paper, a numerical investigation is conducted on a CTES system mounted in a freezer to find out the effective phase change material (PCM) volume. A large amount of the cold thermal energy is stored as latent heat during solidification of eutectic solution NaCl-H2O as PCM with −21 °C melting temperature. This latent cold thermal energy is then released into the freezer compartment when the compressor of the refrigeration cycle is off. Because of the space limitation in freezer cabin, CTES system should be designed as much as compact and efficient. Thereby, PCM boxes with the maximum exposed area and different PCM thicknesses of 0.5, 1, 2, 3, 4, 5 and 6 cm are simulated using computational fluid dynamics (CFD) method. The total discharged cold thermal energy, as well as its period, was obtained for all 7 PCM thicknesses. Discharging time per unit of PCM mass (τdisch) is introduced as the ratio of the discharging time of PCM (time of off-compressor) to the total PCM mass to comparison the effectiveness of CTES system. It is revealed that the τdisch does not rise with the PCM volume, proportionally. Just when the PCM thickness is raised from 2 cm to 3 cm, the τdisch improved significantly for 45% and weakly increased afterward. It means that container with 3 cm thickness would be the best one for this type of storage system.

In this paper, the influence of hydrogen addition or substitution on Conventional Diesel Combustion (CDC) and Reactivity Controlled Compression Ignition (RCCI) combustion at 1208 and 1300 rpm on medium load, without exhaust gas recirculation (EGR) in Caterpillar 3401 heavy-duty diesel engine is numerically investigated. Different parameters of the ringing intensity, heat efficiency, heat release, cylinder pressure variations, CO, soot, UHC, NOx and CO2 emissions are studied and compared with and without hydrogen combustion. It results that in CDC at 1208 rpm, if hydrogen is substituted to 40.2% of diesel input energy, the emission of CO, soot, UHC, NOx and CO2 greenhouse will decrease to 98%, 27%, 99%, 13% and 38%, respectively; however, indicated work suffers 1% reduction. On the other hand, in all states of hydrogen addition in CDC at 1208 rpm, all pollutant emissions increase, but, this addition leads to increasing of output work. In the best case when hydrogen is added to diesel by 55% of input energy, work increases by 43%; however, when hydrogen is added over than 55% of input energy, knocking will happen. In RCCI combustion, when hydrogen is added or substituted, instead of methane and diesel respectively, methane combustion will improve and emissions except NOx, will reduce. Hydrogen addition in RCCI combustion at 1300 rpm causes the increment of chamber reactivity, which leading to advance the ignition and hasten the rate of temperature and pressure rise in the chamber. The important result is that the hydrogen substitution more than 11% of input energy for methane, and hydrogen addition more than 60% of input energy for diesel cause knocking phenomenon in RCCI engine. In the final, to make a comprehensive comparison the performance and pollutions of gasoline-diesel, methane-diesel, methane-diesel-hydrogen and diesel-hydrogen combustions in this engine are compared among several studies.

One of the promising methods to increase exergoeconomic performance and decrease effects of environmental adverse of energy systems is integration of energy systems. Gas turbine power plant is one of the favorable power generation systems because of its acceleration in start-up and low investment cost. However, the thermal efficiency of gas turbine cycle is low because of the significant heat loss due to high-temperature effluent gas exhausted from the stack. Therefore, if this huge heat loss is recovered by another heat engine coupled with gas turbine cycle the total efficiency will increase, considerably. Stirling engine owing to its high efficiency is one of the promising candidates which can be used as a part of the combined system. Hence, an optimization analysis on standalone gas turbine cycle, as well as combined cycle of gas turbine and Stirling engine are considered in this paper to find out the optimal operational point, thermodynamically and economically. Both single-objective and multi-objective genetic algorithm is performed to optimize the overall plant parameters, subjecting three optimization scenarios of maximizing exegetic efficiency, minimizing levelized cost of electricity and exergo-economic optimization. A comprehensive comparison of gas turbine and Stirling engine combined cycle and standalone gas turbine cycle was performed for these optimization scenarios. Results show a significant improvement in power output and reduction of levelized cost of electricity in combined cycle of gas turbine and Stirling engine. In the optimal point of this hybrid system, levelized cost of electricity reduces by 10.3% and exergetic efficiency improves by 16.1% compared with the optimal point of standalone gas turbine cycle.

High energy demand, and excessive consumption of natural resources, have become one of the most critical global challenges. The building sector is one of the most energy consumers, and it almost consumes one-third of final energy worldwide. Hence, it is one of the most significant CO2 emission sectors. Utilization the renewable energy in building such as solar energy connected with latent thermal energy storage (LTES) using phase change materials (PCM) is a promising solution to reduce conventional energy consumption and diminish greenhouse gas emissions. Separately, a proper heating system selection preparing a comfortable heating condition is a priority. Underfloor heating systems (UFHSs) can maintain indoor air temperature more comfortably than other heating systems. This study used parabolic trough solar collector (PTSC) as a heating source for two test cubicles equipped with underfloor heating systems. In situ latent energy storage using hydrate salt with 32 °C melting temperature is used in one test cubicle and it compared with the typical underfloor heating system embedding pipes under sand in the other same cubicle. Results revealed that the latent thermal energy stored in PCM can maintain the indoor air temperature of the cubicle in comfortable condition for more than 4 h after sunset. Furthermore, PTSC provides more than 80% of cubicles heating loads during the coldest time in Tehran, Iran.

Having great resources of fossil fuels in Iran and ease of access to them inhibits utilization of renewable energies, especially in large scales. In spite of great sources of fossil fuels, Sistan province in the southeast of Iran has no gas pipelines yet and people sometimes use gas cylinders or oil products for heating of their houses. This paper aims to propose a sustainable renewable energy system to provide heating systems for residential buildings as well as domestic hot water (DHW). Five different combinations of solar assisted ground source heat pump (SAGSHP) are simulated for a residential building in the city of Zahedan, Iran. Modeling, simulation, and operation controlling have been performed in TRNSYS software and the coefficient of performance (COP), electrical power consumption of the GSHP, soil temperature, as well as building and domestic hot water temperatures for 10 years of operation have been obtained and compared. It is obtained that a 12 kW GSHP with the assisted flat solar collectors can supply space heating demand and DHW for the building throughout the winter. The maximum and minimum annual mean COP values are 3.75 and 3.52, respectively. In the best scenario for the system assisted with the solar collector, the energy consumption diminishes 8.7% compared to GSHP standalone system.

Freezer is one of the electrical components that can be found in any building. Like any electrical appliance domestic freezer consumes a significant amount of energy during its working time. During recent decades a lot of solutions have been found to reduce this energy consumption. One of the most usable and appropriate ones is implementation of phase change material (PCM) in a Cold Thermal Energy Storage (CTES) system which can be installed in a household freezers. In this paper numerical investigation of using CTES system in a domestic freezer in order to diminish energy consumption during pick hours (18-22:30), is studied. Regard to the temperature ranges of the freezer , NaCl-H 2 O is used as a PCM in the CTES system. In a distinct period of time, a large amount of cold thermal energy in latent heat form is stored at low temperature in the PCM, and it is released in the freezer’s cabin when the compressor is off. Accordingly, numerical modeling and simulation using Computational Fluid Dynamics (CFD) software on charging and discharging cycle of PCM are done to measure cold storage period and amount of saved energy. The results reveal that using CTES could keep the freezer in the standard thermal condition without using a compressor , for 4.5 hours. These results show that if the PCM used in CTES system for a year, it could reduce energy, fossil fuel consumption and CO 2 emission up to 45.7 kWh, 13.7 liters and 32.0 kg, respectively.

One of the promising ways for solving the water scarcity's problem in the world is distillation of the ocean's salt water by thermal methods. This method can be competitive with other methods, if required thermal energy is supplied by recovering the heat wastes of other energy systems such as gas turbine (GT) power plant. In this paper, a combined cycle of solid oxide fuel cell (SOFC) and GT can be used as thermal resource of multiple effect desalination system. Combination of these three system leads to reduce in total energy consumption, reduce in exhaust pollutants and reduce in operation and maintenance cost as well as increasing total efficiency in comparison with conventional individual systems. Exergoeconomic analysis of this hybrid system was performed to find out technical and economical optimal working point. The system costs and revenues estimated, and the effect of two important design parameters (i.e., operational temperature and current density of SOFC) on exergy efficiency and levelized cost of electricity (LCOE) were investigated. Implementing GA optimization on the system and calculating the optimal values of the design parameter leads to rise of the exergy efficiency from 57% up to 63.5% and levelized cost of electricity was decreased to 0.0643 $/kwh.

Power efficiency of Photovoltaic (PV) cell reduce due to the warm up under solar irradiation. Several passive and active cooling experimental investigations are implemented on a PV cell in this study to find out their impacts on the electrical and thermal performance of a PVT system. All experiments are performed in a solar simulator under a wide range (regular-concentrated) of solar radiation power (800–1700 W m−2). PCM is used as passive coolant system, whereas to overcome the malfunction of PCM, due its low thermal conductivity, PCM is infiltered in a special heat conductive foam (PS-CNT foam). Results revealed that PCM-composite can diminish the PV-cell temperature up to 6.8% and increase electrical effciciency up to 14.%. Separately, active cooling are examined by passing water with the range of 0.3–1 lit.min−1 through a cooling block mounted undre the PVT system. In the active cooling system, due to the efficient electrical power generation as well as harvesting thermal energy, the system performance is much higher than passive PVT systems. The best PVT system examined in this study is the PV-PCM-composite system which its energy efficiencies in the active cooling is 66.8–82.6%.

The well-testing model identification is a challenging task due to non-uniqueness of the pressure responses generated by different reservoir models. An automated framework is very useful to aid in diagnosing the well-testing interpretation models. Since the well-testing diagnostic plots are arranged nearly ordered in time, the well-testing model recognition could be considered as a time-series classification problem where different types of underlying reservoir models constitute different classes. A novel approach is proposed for the well-testing model identification from the pressure transient test data using the concept of shapelets in this article. Shapelets defined as time series subsequences which are in some sense maximally representatives of a class have been recently developed and used in time series classification and clustering problems. Five different well-testing models (or classes) are investigated in this article. Shapelets are initially extracted for each pair of classes using the Fast-Shapelet algorithm and the minimum distances from the time series objects to the extracted shapelets are calculated to form a new feature space. Classification is applied on the new feature space using four different binary classifiers including random forest (RF), support vector machine (SVM), logistic regression (LR) and probabilistic neural network (PNN). The results verify that the RF technique yields the highest F-score value in predicting the true class labels among all the binary classifiers. To further improve the classification performance, an ensemble learner is finally created using the individual classifiers. The proposed approach is validated by testing against several real field test data. The results indicate that the shapelet-based approach is promising for the well-testing diagnosis applications.

Given exterior walls as the main drawback of buildings, the present experimental study was conducted to investigate the effect of phase-change material (PCMs) as the building envelope layer on the thermal effectiveness and indoor air conditioning. Two 1 × 1 m2 cubicles with the same geometry, orientation and construction materials were built as an experimental set-up while adding a PCM layer to the walls of only one of the cubicles referred to as the PCM cubicle and leaving the other wall layers unchanged. The other cubicle is referred to as the Ref. cubicle. Several K-type thermocouples were mounted within the layers at the centre of both cubicles. The same air cooler used to match the indoor conditions of the two cubicles at the beginning of all the examinations was shut down after achieving the desirable temperature at their centre to allow the environment to naturally change the indoor conditions of the cubicles. The indoor cubicle temperature as well as temperature at the interface of layers are acquired. The data collected within nine days respectively showed reductions of 1.5 and 2.3°C in the average and peak indoor air temperature of the PCM cubicle in summer compared to those of the Ref. cubicle. Using the PCM panel in the eastern wall (hot wall) also decreased the heat gain by 44%.

A different approach based on existing spatiotemporal models is developed in this research for forecasting the production flow rates of a group of adjacent wells in a reservoir. Unlike the previous single-well analysis techniques, this new methodology tries to forecast the flow rates of a number of producing wells located in a certain neighborhood. It also takes into account the variety of flow rate patterns that may take place during the production period of the wells. Regarding the time-series nature of flow rate data and the spatial relationships between multiple wells in a proximity, the Space-Time Auto-Regressive Moving-Average technique, abbreviated as STARMA, is borrowed to employ in this research to capture the spatial inter-relationships of the wells and model the flow rate data of multiple wells simultaneously. Partitioning the field into different groups of adjacent wells based on the similarity of flow rate patterns is also recommended using the spatial clustering algorithms as an enhancing part of the proposed methodology. The capability of the proposed approach in forecasting the flow rates of multiple wells is verified using the real data of a case study including 38 active oil producing wells located in a reservoir in South West Iran. The forecasts generated by the proposed method are finally compared with the predictions obtained by the current ARIMA techniques. Based on findings of this research, the proposed space time modeling of multiple well flow rates helps in estimating the more accurate forecasts, when the single well analysis techniques fail in predicting the real trend of future flow rates.

This paper examines the thermal properties of pure tetracosane paraffin, tetracosane-graphene, and tetracosane-carbon nanotube mixed phase change materials (PCM). The most important properties studied were thermal capacity in constant volume (Cv), mean square displacement of atoms (MSD), radial distribution function (RDF), density, phonon density of states (PDOS) and thermal conductivity (k) under different temperatures. The results show that graphene and carbon nanotube increase the thermal conductivity of the tetracosane at different temperatures, but decrease the molecular movement and its thermal capacity (except after about 360 K), and it can be said that this slightly decreases the paraffin melting temperature. It was demonstrated that carbon nanotube is more efficient than graphene to increase the thermal conductivity of the proposed PCM.