4E Advancement of Heat Recovery During Hot Seasons for a Building Integrated Photovoltaic Thermal (BIPV/T) System

In conventional building integrated photovoltaic thermal (BIPV/T) systems, heat is only recovered during cold seasons. However, no recovery takes place in hot seasons. Therefore, this study comes up with an answer to the question “how much improvement in the amount of annual recovered heat (ANRH), average exergy efficiency (AAEE), and CO2 saving (ACDS), as well as payback period (PBP), is achieved when heat recovery is done in hot seasons?”. These are representatives of energy, exergy, environmental and economic (4E) aspects, respectively. The results show a 135.6%, 1.8% and 123.0% enhancement in the ANRH, AAEE and ACDS, respectively, while PBP decreases from 6.10 to 3.94 years

An artificial intelligence-based prediction way to describe flowing a Newtonian liquid/gas on a permeable flat surface

The purpose of this study is to utilize artificial neural network (ANN), as one of the most powerful artificial intelligence methods, for modeling stream function (f) and the dimensionless temperature (θ) for the considered problem. The problem that is investigated here is flowing a Newtonian fluid on a permeable flat surface. The Homotopy Perturbation Method (HPM) recently developed by the authors for this problem is utilized to provide enough number of the input data. The best ANN is found for each of the two indicated outputs. Then, the best ANN model for each output is utilized to investigate the impact of changing the similarity variable in the range 0.0 to 10.0 on prediction error of the two mentioned outputs. Four values for porosity, which are 0.2, 0.5, 0.8, and 1.0, are investigated. According to the findings, an almost quadratic relation for changes prediction error of f as a function of η is seen, whereas after a sudden drop, the error in prediction of θ declines linearly. Moreover, for the whole range, and for both outputs, the error remains in an acceptable range, which verifies the good accuracy of ANN.http://link.springer.com/journal/10973hj2022Mechanical and Aeronautical Engineerin

Closest Match Based Information Retrieval and Recommendation Engine using Signature-Trees and Fuzzy Relevance Sorting

This paper proposes a recommendation technique to avoid exhaustive search to be ran on the database with thousands of records, before coming to a conclusion or inference, where it can be said that recommended thing is matching up to a significant percentage of what was initially desired. Often such searches involve not just the simple full-match search based on indexes, but also the partial or nearby match searches where which percentage of match between entities is relevant enough for ultimate recommendation. Usually these problems are tackled by various methods like Fuzzy operations, Reg-Ex searches, Clustering, Similarity Analysis each having its own set of effectiveness as well as efficiency. Our goal here was to create a search and recommendation system which can perform fuzzy-search and fuzzy-similarity-analysis with near-match percentages in an effective, efficient as well as user-friendly manner on thousands of records/ files/ rows with 100s of attributes/ features/ columns. Inspired from Google's Image Searching Algorithm, that search on the basis of signatures based on feature-extraction from each image, we have created Match engine, that read schema of data or files, compiles encoded signature and store them as an index. That index is then converted into a tree (S-Tree), on the basis of relevance of each field/ column and data frequency observed. After compilation done, system can now search and recommendation of best matches in very efficient manner. For further optimization we use heuristics like dividing feature sets into hard-filters and soft-filters, former demands full match and later demands fuzzy match. On arriving even one best match, we can retrieve other matches without searching.Our technique though not that modern and actually inspired, but based on ensemble methods used to provide fast and efficient results. We have proved quicker than full scan searches. In future we plan to make signature comparison engine on variety of advanced data types of features like Geo-coordinates and synonyms. And storing compiled signatures trees into distributed database/grid, query will run concurrently to match the results, or signatures passing through machine learning techniques. Currently system used for recipe recommendation and in future this will be used in applications like dating system’s, film and music recommendation

Performing an 'Athletic Movement Assessment' for Sports Jump Using State of the Art Video Analysis and Heuristics Techniques Like Body Detection and Displacement Assessment

This paper proposes a some novel and state of the art technique for analyzing the Athletic Movement (Vertical Jump) and feats  by analyzing video frame by frame.  Most common method to analyze "Athletic Movement" such as Jump and feats accomplished in them are either an observations made by an human expert / coach, or they are the values captured by measurement devices in the suit or wearables attached to the body of an athlete. Where former requires an access to the human expert, the later requires the special kind of a hardware / sensor that has capability to extract the body movement statistics with respect to time and space. Both methods are pretty accurate but due to their overhead in terms of necessity / dependence on 3rd party system or person. Not to mention along with the cost such methods come up with, they are often inaccessible in situations where one's just home practicing or when an athlete is just trying out something in own backyard or Gym (personal zones). Our target was here to reduce those dependencies and create such heuristics and algorithms that can help an individual athlete to assess the feats like Jump, Run, and Leap, without using any 3rd party systems, and be able to approximate the feats and compare them with the existing ones using only the cellphone device in their pocket. This paper focused on Jump sport. The system processed video frame by frame and Applying Histogram Of Oriented Gradient Technique to find Human in Frame and then track human from  initial to last and we are capable now to calculate pixel distance covered by human in Jump. We used some values like human height to find physical distance covered, Frame Per Frame (FPS) of video, Markers on screen of mobile while recording videos.To validate the algorithm results, a number of experiments were performed and then compare with the actual vertical jump height and derive a statistical relation between the proposed methodology and the traditional techniques. Proposed technique can also be used for calculating different statistics of sport person

Modeling and exergy analysis of domestic MED desalination with brine tank

Desalination systems are taken into account as one of the promising solutions to deal with the water scarcity problem. Among different kinds of desalination systems, having the advantages like using low grade thermal resources, multi-effect type is getting popular more and more. Considering the mentioned issues, in this study, a high performance multi-effect desalination (MED) system is introduced and the enhancement potential of that is evaluated in details. The introduced and reference designs are compared together from different points of view. The results showed that not only the fresh water production of the introduced MED device is enhanced from the range of 12–16 to 14–21.6 L h–1 compared to the base case condition, but also gained output ratio increases up to 30%–40%. Moreover, the conducted exergy analysis shows that with the exergy efficiency of 82%, the brine tank has the highest performance among other components, while the exergy destruction for this part is negligible compared to the other parts. Therefore, a high level of improvement can be achieved using the introduced design.https://www.deswater.compm2020Mechanical and Aeronautical Engineerin

Applying homotopy perturbation method to provide an analytical solution for Newtonian fluid flow on a porous flat plate

This research work is going to apply the homotopy perturbation method to solve the problem of flowing Newtonian fluid on a flat plate. For this purpose, initially, the problem, including the governing equations and boundary conditions, is defined, and after that, the considered assumptions to solve the defined problem are introduced. Next, the working principle of the homotopy perturbation method is described, and then, the way to obtain the analytical solution using the homotopy perturbation method is presented, and finally, the accuracy of the proposed analytical solution in comparison to the numerical approach is compared for validation. Both momentum and energy equations are solved. The maple software program is utilized for carrying out the mathematical calculations, while the validation is done using the profiles for stream function, velocity distribution, stress, and dimensionless temperature as the key indicators related to the solution. The conducted comparison shows that the analytical solution provided by the homotopy perturbation method is able to predict all the important performance criteria for the problem very well, and therefore, the homotopy perturbation method has a strong potential to be employed for providing the analytical solution for such problems.http://wileyonlinelibrary.com/journal/mma2022-02-05hj2021Mechanical and Aeronautical Engineerin

A smart load-speed sensitive cooling map to have a high- performance thermal management system in an internal combustion engine

Considering the fact that electrification is increasingly used in internal combustion engines, this paper aims at presenting a smart speed-load sensitive cooling map for better thermal management. For this purpose, first, thermal boundary conditions for the engine cooling passage were obtained by thermodynamic and combustion simulation. Next, the temperature distribution of the cooling passage walls was determined using conjugate heat transfer method. Then, the effect of engine load on wall temperature distribution was investigated, and it was observed that in the conventional mode where the cooling flow is only affected by the engine speed, the engine is faced with over-cooling and under-cooling. Therefore, the optimum flow for cooling the engine was achieved in such a way that the engine is hot enough and kept free from damage, while the engine has a more uniform temperature distribution. These calculations were performed by considering the boiling phenomenon. The results showed using the cooling map leads to a significant reduction in coolant flow, which in turn reduces the power consumption of the water pump and size of the radiator. Moreover, fuel consumption, hydrocarbon emission production, and the needed power of the coolant pump are enhanced by 2.1, 8.6, and 44.3%, respectively.Irankhodro Powertrain Company (IPCo)http://www.elsevier.com/locate/energy2022-04-22hj2021Mechanical and Aeronautical Engineerin

4E Advancement of Heat Recovery during Hot Seasons for a Building Integrated Photovoltaic Thermal (BIPV/T) System

In conventional building integrated photovoltaic thermal (BIPV/T) systems, heat is only recovered during cold seasons. However, no recovery takes place in hot seasons. Therefore, this study comes up with an answer to the question “how much improvement in the amount of annual recovered heat (ANRH), average exergy efficiency (AAEE), and CO2 saving (ACDS), as well as payback period (PBP), is achieved when heat recovery is done in hot seasons?”. These are representatives of energy, exergy, environmental and economic (4E) aspects, respectively. The results show a 135.6%, 1.8% and 123.0% enhancement in the ANRH, AAEE and ACDS, respectively, while PBP decreases from 6.10 to 3.94 years

Deep Q-Value Neural Network (DQN) Reinforcement Learning for the Techno-Economic Optimization of a Solar-Driven Nanofluid-Assisted Desalination Technology

A solar-driven desalination system, featuring a single-slope solar still is studied here. For this design, Al2O3 nanofluid is utilized, and the condition achieving the highest efficiency and cost-effectiveness is found using a reinforcement learning called a deep Q-value neural network (DQN). The results of optimization are implemented for the built experimental setup. Experimental data obtained under the climatic conditions of Tehran, Iran, are employed to compare the enhancement potential of the optimized solar still system with nanofluid (OSTSWNF) with the solar still system with water (STSWWA). The hourly fluid temperatures in the basin as well as the hourly and cumulative freshwater production (HFWP and CFWP) are discussed. A number of other parameters, including daily water production and efficiency in addition to the cost per liter (CPL) of the resulting desalinated water, are also taken into account. The results reveal that annual water production increases from 1326.8 L to 1652.4 L, representing ~25% growth. Moreover, the annual average efficiency improves by ~32%, rising from 41.6% to 54.7%. A great economic enhancement is seen as well, with the CPL decreasing by ~8%, i.e., from USD 0.0258/L to USD 0.0237/L